Paper Digest: Recent Papers on Machine Translation
Paper Digest Team extracted all recent Machine Translation related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic. Based in New York, Paper Digest is dedicated to producing high-quality text analysis results that people can acturally use on a daily basis. In the past 4 years, we have been serving users across the world with a number of exclusive services on ranking, search, tracking and review. This month we feature Literature Review Generator, which automatically generates literature review around any topic.
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TABLE 1: Paper Digest: Recent Papers on Machine Translation
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | VISA: An Ambiguous Subtitles Dataset for Visual Scene-Aware Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce VISA, a new dataset that consists of 40k Japanese-English parallel sentence pairs and corresponding video clips with the following key features: (1) the parallel sentences are subtitles from movies and TV episodes; (2) the source subtitles are ambiguous, which means they have multiple possible translations with different meanings; (3) we divide the dataset into Polysemy and Omission according to the cause of ambiguity. |
Yihang Li; Shuichiro Shimizu; Weiqi Gu; Chenhui Chu; Sadao Kurohashi; | arxiv-cs.CL | 2022-01-20 |
| 2 | Linguistically-driven Multi-task Pre-training for Low-resource Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the present study, we propose novel sequence-to-sequence pre-training objectives for low-resource machine translation (NMT): Japanese-specific sequence to sequence (JASS) for language pairs involving Japanese as the source or target language, and English-specific sequence to sequence (ENSS) for language pairs involving English. |
Zhuoyuan Mao; Chenhui Chu; Sadao Kurohashi; | arxiv-cs.CL | 2022-01-20 |
| 3 | Klexikon: A German Dataset for Joint Summarization and Simplification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this problem, we pose core requirements for a system that can jointly summarize and simplify long source documents. |
Dennis Aumiller; Michael Gertz; | arxiv-cs.CL | 2022-01-18 |
| 4 | Syntax-based Data Augmentation for Hungarian-English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We train Transformer-based neural machine translation models for Hungarian-English and English-Hungarian using the Hunglish2 corpus. |
Attila Nagy; Patrick Nanys; Balázs Frey Konrád; Bence Bial; Judit Ács; | arxiv-cs.CL | 2022-01-18 |
| 5 | Improving Neural Machine Translation By Denoising Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a simple and effective pretraining strategy {D}en{o}ising {T}raining DoT for neural machine translation. |
Liang Ding; Keqin Peng; Dacheng Tao; | arxiv-cs.CL | 2022-01-18 |
| 6 | Towards The Next 1000 Languages in Multilingual Machine Translation: Exploring The Synergy Between Supervised and Self-Supervised Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we present a pragmatic approach towards building a multilingual MT model that covers hundreds of languages, using a mixture of supervised and self-supervised objectives, depending on the data availability for different language pairs. |
ADITYA SIDDHANT et. al. | arxiv-cs.CL | 2022-01-09 |
| 7 | An Ensemble Approach to Acronym Extraction Using Transformers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper discusses an ensemble approach for the task of Acronym Extraction, which utilises two different methods to extract acronyms and their corresponding long forms. |
Prashant Sharma; Hadeel Saadany; Leonardo Zilio; Diptesh Kanojia; Constantin Orăsan; | arxiv-cs.CL | 2022-01-09 |
| 8 | Phrase-level Adversarial Example Generation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a phrase-level adversarial example generation (PAEG) method to enhance the robustness of the model. |
JUNCHENG WAN et. al. | arxiv-cs.CL | 2022-01-06 |
| 9 | How Do Lexical Semantics Affect Translation? An Empirical Study Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we investigate these relationships on a variety of low-resource language pairs from the OpenSubtitles2016 database, where the source language is English, and find that the more similar the target language is to English, the greater the translation performance. |
Vivek Subramanian; Dhanasekar Sundararaman; | arxiv-cs.CL | 2021-12-31 |
| 10 | Frequency-Aware Contrastive Learning for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we propose a frequency-aware token-level contrastive learning method, in which the hidden state of each decoding step is pushed away from the counterparts of other target words, in a soft contrastive way based on the corresponding word frequencies. |
TONG ZHANG et. al. | arxiv-cs.CL | 2021-12-29 |
| 11 | A Preordered RNN Layer Boosts Neural Machine Translation in Low Resource Settings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to augment attention based neural network with reordering information to alleviate the lack of data. |
Mohaddeseh Bastan; Shahram Khadivi; | arxiv-cs.CL | 2021-12-27 |
| 12 | HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce HOPE, a task-oriented and human-centric evaluation framework for machine translation output based on professional post-editing annotations. |
Serge Gladkoff; Lifeng Han; | arxiv-cs.CL | 2021-12-27 |
| 13 | Few-shot Learning with Multilingual Language Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we train multilingual autoregressive language models on a balanced corpus covering a diverse set of languages, and study their few- and zero-shot learning capabilities in a wide range of tasks. |
XI VICTORIA LIN et. al. | arxiv-cs.CL | 2021-12-20 |
| 14 | Challenge Dataset of Cognates and False Friend Pairs from Indian Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe the creation of two cognate datasets for twelve Indian languages, namely Sanskrit, Hindi, Assamese, Oriya, Kannada, Gujarati, Tamil, Telugu, Punjabi, Bengali, Marathi, and Malayalam. |
Diptesh Kanojia; Pushpak Bhattacharyya; Malhar Kulkarni; Gholamreza Haffari; | arxiv-cs.CL | 2021-12-17 |
| 15 | Isometric MT: Neural Machine Translation for Automatic Dubbing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work, introduces a self-learning approach that allows a transformer model to directly learn to generate outputs that closely match the source length, in short isometric MT. In particular, our approach for isometric MT does not require to generate multiple hypotheses nor any auxiliary scoring function. |
Surafel M. Lakew; Yogesh Virkar; Prashant Mathur; Marcello Federico; | arxiv-cs.CL | 2021-12-16 |
| 16 | Learning and Analyzing Generation Order for Undirected Sequence Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we train a policy that learns the generation order for a pre-trained, undirected translation model via reinforcement learning. |
Yichen Jiang; Mohit Bansal; | arxiv-cs.CL | 2021-12-16 |
| 17 | Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate the use of cross-lingual word embeddings for detecting cognates among fourteen Indian Languages. |
DIPTESH KANOJIA et. al. | arxiv-cs.CL | 2021-12-16 |
| 18 | Learning Cross-Lingual IR from An English Retriever Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new cross-lingual information retrieval (CLIR) model trained using multi-stage knowledge distillation (KD). |
YULONG LI et. al. | arxiv-cs.CL | 2021-12-15 |
| 19 | Lesan — Machine Translation for Low Resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Lesan, an MT system for low resource languages. |
Asmelash Teka Hadgu; Abel Aregawi; Adam Beaudoin; | arxiv-cs.CL | 2021-12-15 |
| 20 | Prosody-Aware Neural Machine Translation for Dubbing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an implicit and explicit modeling approaches to integrate prosody information into neural machine translation. |
Derek Tam; Surafel M. Lakew; Yogesh Virkar; Prashant Mathur; Marcello Federico; | arxiv-cs.CL | 2021-12-15 |
| 21 | Massive-scale Decoding for Text Generation Using Lattices Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a search algorithm to construct lattices encoding a massive number of generation options. |
Jiacheng Xu; Greg Durrett; | arxiv-cs.CL | 2021-12-14 |
| 22 | Step-unrolled Denoising Autoencoders for Text Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a new generative model of text, Step-unrolled Denoising Autoencoder (SUNDAE), that does not rely on autoregressive models. |
Nikolay Savinov; Junyoung Chung; Mikolaj Binkowski; Erich Elsen; Aaron van den Oord; | arxiv-cs.CL | 2021-12-13 |
| 23 | Communication-Efficient Federated Learning for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore how to efficiently build NMT models in an FL setup by proposing a novel solution. |
Tanya Roosta; Peyman Passban; Ankit Chadha; | arxiv-cs.CL | 2021-12-11 |
| 24 | Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specific use-cases are usually left out, since generic models tend to perform poorly in domain-specific cases. |
Javad Pourmostafa Roshan Sharami; Dimitar Shterionov; Pieter Spronck; | arxiv-cs.CL | 2021-12-11 |
| 25 | Translating Politeness Across Cultures: Case of Hindi and English Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a corpus based study of politeness across two languages-English and Hindi. |
Ritesh Kumar; Girish Nath Jha; | arxiv-cs.CL | 2021-12-03 |
| 26 | Multitask Finetuning for Improving Neural Machine Translation in Indian Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a Multitask Finetuning methodology which combines the Bilingual Machine Translation task with an auxiliary Causal Language Modeling task to improve performance on the former task on Indian Languages. |
Shaily Desai; Atharva Kshirsagar; Manisha Marathe; | arxiv-cs.CL | 2021-12-03 |
| 27 | Improvement in Machine Translation with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore machine translation improvement via Generative Adversarial Network (GAN) architecture. |
Jay Ahn; Hari Madhu; Viet Nguyen; | arxiv-cs.CL | 2021-11-30 |
| 28 | Ensembling of Distilled Models from Multi-task Teachers for Constrained Resource Language Pairs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our submission to the constrained track of WMT21 shared news translation task. |
AMR HENDY et. al. | arxiv-cs.CL | 2021-11-25 |
| 29 | Boosting Neural Machine Translation with Dependency-Scaled Self-Attention Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose a novel, parameter-free, dependency-scaled self-attention network, which integrates explicit syntactic dependencies into the attention network to dispel the dispersion of attention distribution. |
Ru Peng; Nankai Lin; Yi Fang; Shengyi Jiang; Junbo Zhao; | arxiv-cs.CL | 2021-11-23 |
| 30 | R-Drop: Regularized Dropout for Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a simple consistency training strategy to regularize dropout, namely R-Drop, which forces the output distributions of different sub models generated by dropout to be consistent with each other. |
XIAOBO LIANG et. al. | nips | 2021-11-20 |
| 31 | BARTScore: Evaluating Generated Text As Text Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we conceptualize the evaluation of generated text as a text generation problem, modeled using pre-trained sequence-to-sequence models. |
Weizhe Yuan; Graham Neubig; Pengfei Liu; | nips | 2021-11-20 |
| 32 | Detecting Cross-Language Plagiarism Using Open Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the new multilingual retrieval model Cross-Language Ontology-Based Similarity Analysis (CL-OSA) for this task. |
JOHANNES STEGMÜLLER et. al. | arxiv-cs.CL | 2021-11-18 |
| 33 | XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents XLS-R, a large-scale model for cross-lingual speech representation learning based on wav2vec 2.0. |
ARUN BABU et. al. | arxiv-cs.CL | 2021-11-17 |
| 34 | NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper provides an overview of NVIDIA NeMo’s neural machine translation systems for the constrained data track of the WMT21 News and Biomedical Shared Translation Tasks. |
Sandeep Subramanian; Oleksii Hrinchuk; Virginia Adams; Oleksii Kuchaiev; | arxiv-cs.CL | 2021-11-16 |
| 35 | Measuring Uncertainty in Translation Quality Evaluation (TQE) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The methodology we applied for this work is from Bernoulli Statistical Distribution Modelling (BSDM) and Monte Carlo Sampling Analysis (MCSA). |
Serge Gladkoff; Irina Sorokina; Lifeng Han; Alexandra Alekseeva; | arxiv-cs.CL | 2021-11-15 |
| 36 | DEEP: DEnoising Entity Pre-training for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this limitation, we propose DEEP, a DEnoising Entity Pre-training method that leverages large amounts of monolingual data and a knowledge base to improve named entity translation accuracy within sentences. |
Junjie Hu; Hiroaki Hayashi; Kyunghyun Cho; Graham Neubig; | arxiv-cs.CL | 2021-11-14 |
| 37 | Sign Language Translation with Hierarchical Spatio-TemporalGraph Neural Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, these unique characteristics of sign languages are formulated as hierarchical spatio-temporal graph representations, including high-level and fine-level graphs of which a vertex characterizes a specified body part and an edge represents their interactions. |
JICHAO KAN et. al. | arxiv-cs.CV | 2021-11-14 |
| 38 | Speeding Up Entmax Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an alternative to $\alpha$-entmax, which keeps its virtuous characteristics, but is as fast as optimized softmax and achieves on par or better performance in machine translation task. |
Maxat Tezekbayev; Vassilina Nikoulina; Matthias Gallé; Zhenisbek Assylbekov; | arxiv-cs.CL | 2021-11-12 |
| 39 | Developing Neural Machine Translation Models for Hungarian-English Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: I propose 5 different augmentation methods that are structure-aware, meaning that instead of randomly selecting words for blanking or replacement, the dependency tree of sentences is used as a basis for augmentation. |
Attila Nagy; | arxiv-cs.CL | 2021-11-07 |
| 40 | HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve effectiveness of the available BT data, we introduce HintedBT-a family of techniques which provides hints (through tags) to the encoder and decoder. |
Sahana Ramnath; Melvin Johnson; Abhirut Gupta; Aravindan Raghuveer; | emnlp | 2021-11-05 |
| 41 | Recurrent Attention for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we push further in this research line and propose a novel substitute mechanism for self-attention: Recurrent AtteNtion (RAN) . |
Jiali Zeng; Shuangzhi Wu; Yongjing Yin; Yufan Jiang; Mu Li; | emnlp | 2021-11-05 |
| 42 | One Source, Two Targets: Challenges and Rewards of Dual Decoding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider a stronger requirement: to jointly generate two texts so that each output side effectively depends on the other. |
Jitao Xu; Fran?ois Yvon; | emnlp | 2021-11-05 |
| 43 | Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a cross-lingual data selection method to extract in-domain sentences in the missing language side from a large generic monolingual corpus. |
Thuy-Trang Vu; Xuanli He; Dinh Phung; Gholamreza Haffari; | emnlp | 2021-11-05 |
| 44 | BiSECT: Learning to Split and Rephrase Sentences with Bitexts Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel dataset and a new model for this ‘split and rephrase’ task. |
Joongwon Kim; Mounica Maddela; Reno Kriz; Wei Xu; Chris Callison-Burch; | emnlp | 2021-11-05 |
| 45 | An Empirical Investigation of Word Alignment Supervision for Zero-Shot Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the benefits of an explicit alignment to language labels in Transformer-based MNMT models in the zero-shot context, by jointly training one cross attention head with word alignment supervision to stress the focus on the target language label. |
Alessandro Raganato; Ra?l V?zquez; Mathias Creutz; J?rg Tiedemann; | emnlp | 2021-11-05 |
| 46 | Rule-based Morphological Inflection Improves Neural Terminology Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a modular framework for incorporating lemma constraints in neural MT (NMT) in which linguistic knowledge and diverse types of NMT models can be flexibly applied. |
Weijia Xu; Marine Carpuat; | emnlp | 2021-11-05 |
| 47 | A Generative Framework for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a generative framework for simultaneous machine translation. |
Yishu Miao; Phil Blunsom; Lucia Specia; | emnlp | 2021-11-05 |
| 48 | Document Graph for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we hypothesize that a document can be represented as a graph that connects relevant contexts regardless of their distances. |
Mingzhou Xu; Liangyou Li; Derek F. Wong; Qun Liu; Lidia S. Chao; | emnlp | 2021-11-05 |
| 49 | Don’t Go Far Off: An Empirical Study on Neural Poetry Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an empirical investigation for poetry translation along several dimensions: 1) size and style of training data (poetic vs. non-poetic), including a zero-shot setup; 2) bilingual vs. multilingual learning; and 3) language-family-specific models vs. mixed-language-family models. |
Tuhin Chakrabarty; Arkadiy Saakyan; Smaranda Muresan; | emnlp | 2021-11-05 |
| 50 | Cross Attention Augmented Transducer Networks for Simultaneous Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel architecture, Cross Attention Augmented Transducer (CAAT), for simultaneous translation. |
Dan Liu; Mengge Du; Xiaoxi Li; Ya Li; Enhong Chen; | emnlp | 2021-11-05 |
| 51 | Vision Matters When It Should: Sanity Checking Multimodal Machine Translation Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a qualitative study that examines the role of datasets in stimulating the leverage of visual modality and we propose methods to highlight the importance of visual signals in the datasets which demonstrate improvements in reliance of models on the source images. |
Jiaoda Li; Duygu Ataman; Rico Sennrich; | emnlp | 2021-11-05 |
| 52 | GFST: Gender-Filtered Self-Training for More Accurate Gender in Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose gender-filtered self-training (GFST) to improve gender translation accuracy on unambiguously gendered inputs. |
Prafulla Kumar Choubey; Anna Currey; Prashant Mathur; Georgiana Dinu; | emnlp | 2021-11-05 |
| 53 | Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we apply one translation per discourse in NMT, and aim to encourage lexical translation consistency for document-level NMT. |
Xinglin Lyu; Junhui Li; Zhengxian Gong; Min Zhang; | emnlp | 2021-11-05 |
| 54 | Documenting Large Webtext Corpora: A Case Study on The Colossal Clean Crawled Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we provide some of the first documentation for the Colossal Clean Crawled Corpus (C4; Raffel et al., 2020), a dataset created by applying a set of filters to a single snapshot of Common Crawl. |
JESSE DODGE et. al. | emnlp | 2021-11-05 |
| 55 | Language Modeling, Lexical Translation, Reordering: The Training Process of NMT Through The Lens of Classical SMT Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we look at the competences related to three core SMT components and find that during training, NMT first focuses on learning target-side language modeling, then improves translation quality approaching word-by-word translation, and finally learns more complicated reordering patterns. |
Elena Voita; Rico Sennrich; Ivan Titov; | emnlp | 2021-11-05 |
| 56 | Unsupervised Neural Machine Translation with Universal Grammar Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we seek to leverage such shared grammar clues to provide more explicit language parallel signals to enhance the training of unsupervised machine translation models. |
Zuchao Li; Masao Utiyama; Eiichiro Sumita; Hai Zhao; | emnlp | 2021-11-05 |
| 57 | Evaluating The Morphosyntactic Well-formedness of Generated Texts Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose L’AMBRE – a metric to evaluate the morphosyntactic well-formedness of text using its dependency parse and morphosyntactic rules of the language. |
ADITHYA PRATAPA et. al. | emnlp | 2021-11-05 |
| 58 | Translating Headers of Tabular Data: A Pilot Study of Schema Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate the research study, we construct the first parallel dataset for schema translation, which consists of 3,158 tables with 11,979 headers written in 6 different languages, including English, Chinese, French, German, Spanish, and Japanese. Also, we propose the first schema translation model called CAST, which is a header-to-header neural machine translation model augmented with schema context. |
Kunrui Zhu; Yan Gao; Jiaqi Guo; Jian-Guang Lou; | emnlp | 2021-11-05 |
| 59 | MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we improve multilingual text-to-text transfer Transformer with translation pairs (mT6). |
ZEWEN CHI et. al. | emnlp | 2021-11-05 |
| 60 | Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose heterogeneous ways of embedding topic information at the sentence level into an NMT model to improve translation performance. |
Weixuan Wang; Wei Peng; Meng Zhang; Qun Liu; | emnlp | 2021-11-05 |
| 61 | Cross-lingual Intermediate Fine-tuning Improves Dialogue State Tracking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we enhance the transfer learning process by intermediate fine-tuning of pretrained multilingual models, where the multilingual models are fine-tuned with different but related data and/or tasks. |
Nikita Moghe; Mark Steedman; Alexandra Birch; | emnlp | 2021-11-05 |
| 62 | Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a simple but effective approach for leveraging Wikipedia for neural machine translation as well as cross-lingual tasks of image captioning and dependency parsing without using any direct supervision from external parallel data or supervised models in the target language. |
Mohammad Sadegh Rasooli; Chris Callison-Burch; Derry Tanti Wijaya; | emnlp | 2021-11-05 |
| 63 | Towards Making The Most of Dialogue Characteristics for Neural Chat Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to promote the chat translation by introducing the modeling of dialogue characteristics into the NCT model. |
YUNLONG LIANG et. al. | emnlp | 2021-11-05 |
| 64 | Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an approach, MultiUAT, that dynamically adjusts the training data usage based on the model’s uncertainty on a small set of trusted clean data for multi-corpus machine translation. |
MINGHAO WU et. al. | emnlp | 2021-11-05 |
| 65 | Enlivening Redundant Heads in Multi-head Self-attention for Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a redundant head enlivening (RHE) method to precisely identify redundant heads, and then vitalize their potential by learning syntactic relations and prior knowledge in the text without sacrificing the roles of important heads. |
Tianfu Zhang; Heyan Huang; Chong Feng; Longbing Cao; | emnlp | 2021-11-05 |
| 66 | Controlling Machine Translation for Multiple Attributes with Additive Interventions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We address these problems by introducing vector-valued interventions which allow for fine-grained control over multiple attributes simultaneously via a weighted linear combination of the corresponding vectors. |
Andrea Schioppa; David Vilar; Artem Sokolov; Katja Filippova; | emnlp | 2021-11-05 |
| 67 | I Wish I Would Have Loved This One, But I Didn’t – A Multilingual Dataset for Counterfactual Detection in Product Review Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider the problem of counterfactual detection (CFD) in product reviews. |
James O?Neill; Polina Rozenshtein; Ryuichi Kiryo; Motoko Kubota; Danushka Bollegala; | emnlp | 2021-11-05 |
| 68 | Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents Wino-X, a parallel dataset of German, French, and Russian schemas, aligned with their English counterparts. |
Denis Emelin; Rico Sennrich; | emnlp | 2021-11-05 |
| 69 | XLEnt: Mining A Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we propose Lexical-Semantic-Phonetic Align (LSP-Align), a technique to automatically mine cross-lingual entity lexica from mined web data. |
Ahmed El-Kishky; Adithya Renduchintala; James Cross; Francisco Guzm?n; Philipp Koehn; | emnlp | 2021-11-05 |
| 70 | PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a high-quality and large-scale Vietnamese-English parallel dataset of 3.02M sentence pairs, which is 2.9M pairs larger than the benchmark Vietnamese-English machine translation corpus IWSLT15. |
Long Doan; Linh The Nguyen; Nguyen Luong Tran; Thai Hoang; Dat Quoc Nguyen; | emnlp | 2021-11-05 |
| 71 | Neural Machine Translation Quality and Post-Editing Performance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Across all models, we found that better MT systems indeed lead to fewer changes in the sentences in this industry setting. |
Vil?m Zouhar; Martin Popel; Ondrej Bojar; Ale? Tamchyna; | emnlp | 2021-11-05 |
| 72 | Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This report describes Microsoft’s machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. |
JIAN YANG et. al. | arxiv-cs.CL | 2021-11-03 |
| 73 | Contextual Semantic Parsing for Multilingual Task-Oriented Dialogues Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose automatic translation of dialogue datasets with alignment to ensure faithful translation of slot values and eliminate costly human supervision used in previous benchmarks. Finally, we present RiSAWOZ English and German datasets, created using our translation methodology. |
Mehrad Moradshahi; Victoria Tsai; Giovanni Campagna; Monica S. Lam; | arxiv-cs.CL | 2021-11-03 |
| 74 | Lingua Custodia’s Participation at The WMT 2021 Machine Translation Using Terminologies Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Lingua Custodia’s submission to the WMT21 shared task on machine translation using terminologies. |
Melissa Ailem; Jinghsu Liu; Raheel Qader; | arxiv-cs.CL | 2021-11-03 |
| 75 | Simultaneous Neural Machine Translation with Constituent Label Prediction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the concept of pre-reordering, we propose a couple of simple decision rules using the label of the next constituent predicted by incremental constituent label prediction. |
Yasumasa Kano; Katsuhito Sudoh; Satoshi Nakamura; | arxiv-cs.CL | 2021-10-26 |
| 76 | Assessing Evaluation Metrics for Speech-to-Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Speech-to-speech translation combines machine translation with speech synthesis, introducing evaluation challenges not present in either task alone. How to automatically evaluate … |
Elizabeth Salesky; Julian Mäder; Severin Klinger; | arxiv-cs.CL | 2021-10-26 |
| 77 | Noisy UGC Translation at The Character Level: Revisiting Open-Vocabulary Capabilities and Robustness of Char-Based Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work explores the capacities of character-based Neural Machine Translation to translate noisy User-Generated Content (UGC) with a strong focus on exploring the limits of such approaches to handle productive UGC phenomena, which almost by definition, cannot be seen at training time. |
José Carlos Rosales Núñez; Guillaume Wisniewski; Djamé Seddah; | arxiv-cs.CL | 2021-10-24 |
| 78 | Discontinuous Grammar As A Foreign Language Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To close the gap, we here extend the framework of sequence-to-sequence models for constituent parsing, not only by providing a more powerful neural architecture for improving their performance, but also by enlarging their coverage to handle the most complex syntactic phenomena: discontinuous structures. |
Daniel Fernández-González; Carlos Gómez-Rodríguez; | arxiv-cs.CL | 2021-10-20 |
| 79 | The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a new corpus for gender identification and rewriting in contexts involving one or two target users (I and/or You) — first and second grammatical persons with independent grammatical gender preferences. |
Bashar Alhafni; Nizar Habash; Houda Bouamor; | arxiv-cs.CL | 2021-10-18 |
| 80 | Towards Making The Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Following this idea, we present SixT++, a strong many-to-English NMT model that supports 100 source languages but is trained once with a parallel dataset from only six source languages. |
GUANHUA CHEN et. al. | arxiv-cs.CL | 2021-10-16 |
| 81 | Evaluation of Abstractive Summarisation Models with Machine Translation in Deliberative Processes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present work on summarising deliberative processes for non-English languages. |
M. Arana-Catania; Rob Procter; Yulan He; Maria Liakata; | arxiv-cs.CL | 2021-10-12 |
| 82 | WeTS: A Benchmark for Translation Suggestion Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: With the corpus we construct, we introduce the Transformer-based model for TS, and experimental results show that our model achieves State-Of-The-Art (SOTA) results on all four translation directions, including English-to-German, German-to-English, Chinese-to-English and English-to-Chinese. To break this limitation, we create a benchmark data set for TS, called \emph{WeTS}, which contains golden corpus annotated by expert translators on four translation directions. |
Zhen Yang; Yingxue Zhang; Ernan Li; Fandong Meng; Jie Zhou; | arxiv-cs.CL | 2021-10-11 |
| 83 | LightSeq2: Accelerated Training for Transformer-based Models on GPUs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present LightSeq2, a system for efficient training of Transformer-based models on GPUs. |
XIAOHUI WANG et. al. | arxiv-cs.CL | 2021-10-11 |
| 84 | Unsupervised Neural Machine Translation with Generative Language Models Only Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show how to derive state-of-the-art unsupervised neural machine translation systems from generatively pre-trained language models. |
JESSE MICHAEL HAN et. al. | arxiv-cs.CL | 2021-10-11 |
| 85 | Machine Translation Verbosity Control for Automatic Dubbing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the problem of controlling the verbosity of machine translation output, so that subsequent steps of our automatic dubbing pipeline can generate dubs of better quality. |
SURAFEL M. LAKEW et. al. | arxiv-cs.CL | 2021-10-07 |
| 86 | On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To gain insight into the role neurons play, we study the activation patterns corresponding to meaning-preserving paraphrases (e.g., active-passive). |
Gal Patel; Leshem Choshen; Omri Abend; | arxiv-cs.CL | 2021-10-06 |
| 87 | The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we instead consider the impact of compression in a data-limited regime. |
Orevaoghene Ahia; Julia Kreutzer; Sara Hooker; | arxiv-cs.CL | 2021-10-06 |
| 88 | Sequence-to-Sequence Lexical Normalization with Multilingual Transformers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a sentence-level sequence-to-sequence model based on mBART, which frames the problem as a machine translation problem. |
Ana-Maria Bucur; Adrian Cosma; Liviu P. Dinu; | arxiv-cs.CL | 2021-10-06 |
| 89 | On The Complementarity Between Pre-Training and Back-Translation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce two probing tasks for PT and BT respectively and find that PT mainly contributes to the encoder module while BT brings more benefits to the decoder. |
XUEBO LIU et. al. | arxiv-cs.CL | 2021-10-05 |
| 90 | Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer By Machine Translation Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a numerical `sentiment-closeness’ measure appropriate for assessing the accuracy of a translated affect message in UGC text by an MT system. |
Hadeel Saadany; Constantin Orasan; Emad Mohamed; Ashraf Tantawy; | arxiv-cs.CL | 2021-09-30 |
| 91 | BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we assess the ability of automatic quality metrics to detect critical machine translation errors which can cause serious misunderstanding of the affect message. |
Hadeel Saadany; Constantin Orasan; | arxiv-cs.CL | 2021-09-29 |
| 92 | EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe the EdinSaar submission to the shared task of Multilingual Low-Resource Translation for North Germanic Languages at the Sixth Conference on Machine Translation (WMT2021). |
Svetlana Tchistiakova; Jesujoba Alabi; Koel Dutta Chowdhury; Sourav Dutta; Dana Ruiter; | arxiv-cs.CL | 2021-09-29 |
| 93 | Text Simplification for Comprehension-based Question-Answering Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate the effect of text simplification in the task of question-answering using a comprehension context. |
Tanvi Dadu; Kartikey Pant; Seema Nagar; Ferdous Ahmed Barbhuiya; Kuntal Dey; | arxiv-cs.CL | 2021-09-28 |
| 94 | Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a cascaded model based on the non-autoregressive Transformer that enables end-to-end training without the need for an explicit intermediate representation. |
EVGENIIA TOKARCHUK et. al. | arxiv-cs.CL | 2021-09-27 |
| 95 | Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We utilize a non-autoregressive transformer and present an end-to-end pivot-based integrated model, enabling training on source-target data. |
EVGENIIA TOKARCHUK et. al. | arxiv-cs.CL | 2021-09-27 |
| 96 | Unsupervised Translation of German–Lower Sorbian: Exploring Training and Novel Transfer Methods on A Low-Resource Language Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the methods behind the systems submitted by the University of Groningen for the WMT 2021 Unsupervised Machine Translation task for German–Lower Sorbian (DE–DSB): a high-resource language to a low-resource one. |
Lukas Edman; Ahmet Üstün; Antonio Toral; Gertjan van Noord; | arxiv-cs.CL | 2021-09-24 |
| 97 | The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the Volctrans’ submission to the WMT21 news translation shared task for German->English translation. |
LIHUA QIAN et. al. | arxiv-cs.CL | 2021-09-23 |
| 98 | The NiuTrans Machine Translation Systems for WMT21 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks. |
SHUHAN ZHOU et. al. | arxiv-cs.CL | 2021-09-21 |
| 99 | One Source, Two Targets: Challenges and Rewards of Dual Decoding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider a stronger requirement: to jointly generate two texts so that each output side effectively depends on the other. |
Jitao Xu; François Yvon; | arxiv-cs.CL | 2021-09-21 |
| 100 | CUNI Systems for WMT21: Terminology Translation Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Charles University submission for Terminology translation Shared Task at WMT21. |
Josef Jon; Michal Novák; João Paulo Aires; Dušan Variš; Ondřej Bojar; | arxiv-cs.CL | 2021-09-20 |
| 101 | The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. |
Shuoyang Ding; Marcin Junczys-Dowmunt; Matt Post; Christian Federmann; Philipp Koehn; | arxiv-cs.CL | 2021-09-17 |
| 102 | Back-translation for Large-Scale Multilingual Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work aims to build a single multilingual translation system with a hypothesis that a universal cross-language representation leads to better multilingual translation performance. |
Baohao Liao; Shahram Khadivi; Sanjika Hewavitharana; | arxiv-cs.CL | 2021-09-17 |
| 103 | Does Summary Evaluation Survive Translation to Other Languages? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To investigate how much we can trust machine translation of such a dataset, we translate the English dataset SummEval to seven languages and compare performance across automatic evaluation measures. |
Spencer Braun; Oleg Vasilyev; Neslihan Iskender; John Bohannon; | arxiv-cs.CL | 2021-09-16 |
| 104 | On The Limits of Minimal Pairs in Contrastive Evaluation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a contrastive evaluation suite for English-German MT that implements this recommendation. |
Jannis Vamvas; Rico Sennrich; | arxiv-cs.CL | 2021-09-15 |
| 105 | UniST: Unified End-to-end Model for Streaming and Non-streaming Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, wefocus on developing a unified model (UniST) which supports streaming and non-streaming ST from the perspective of fundamental components, including training objective, attention mechanism and decoding policy. |
Qianqian Dong; Yaoming Zhu; Mingxuan Wang; Lei Li; | arxiv-cs.CL | 2021-09-15 |
| 106 | Miðeind’s WMT 2021 Submission Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Mi{\dh}eind’s submission for the English$\to$Icelandic and Icelandic$\to$English subsets of the 2021 WMT news translation task. |
Haukur Barri Símonarson; Vésteinn Snæbjarnarson; Pétur Orri Ragnarsson; Haukur Páll Jónsson; Vilhjálmur Þorsteinsson; | arxiv-cs.CL | 2021-09-15 |
| 107 | Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we extend the definition of glass-box QE generally to uncertainty quantification with both black-box and glass-box approaches and design several features deduced from them to blaze a new trial in improving QE’s performance. |
KE WANG et. al. | arxiv-cs.CL | 2021-09-15 |
| 108 | Netmarble AI Center’s WMT21 Automatic Post-Editing Shared Task Submission Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Netmarble’s submission to WMT21 Automatic Post-Editing (APE) Shared Task for the English-German language pair. |
Shinhyeok Oh; Sion Jang; Hu Xu; Shounan An; Insoo Oh; | arxiv-cs.CL | 2021-09-14 |
| 109 | Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose CorefCL, a novel data augmentation and contrastive learning scheme based on coreference between the source and contextual sentences. |
Yongkeun Hwang; Hyungu Yun; Kyomin Jung; | arxiv-cs.CL | 2021-09-13 |
| 110 | Rethinking Zero-shot Neural Machine Translation: From A Perspective of Latent Variables Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a denoising autoencoder objective based on pivot language into traditional training objective to improve the translation accuracy on zero-shot directions. |
WEIZHI WANG et. al. | arxiv-cs.CL | 2021-09-10 |
| 111 | Neural Machine Translation Quality and Post-Editing Performance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Across all models, we found that better MT systems indeed lead to fewer changes in the sentences in this industry setting. |
Vilém Zouhar; Aleš Tamchyna; Martin Popel; Ondřej Bojar; | arxiv-cs.CL | 2021-09-10 |
| 112 | Collecting A Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we find grammatical patterns indicating stereotypical and non-stereotypical gender-role assignments (e.g., female nurses versus male dancers) in corpora from three domains, resulting in a first large-scale gender bias dataset of 108K diverse real-world English sentences. |
Shahar Levy; Koren Lazar; Gabriel Stanovsky; | arxiv-cs.CL | 2021-09-08 |
| 113 | Infusing Future Information Into Monotonic Attention Through Language Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Simultaneous neural machine translation(SNMT) models start emitting the target sequence before they have processed the source sequence. |
Mohd Abbas Zaidi; Sathish Indurthi; Beomseok Lee; Nikhil Kumar Lakumarapu; Sangha Kim; | arxiv-cs.CL | 2021-09-07 |
| 114 | IndicBART: A Pre-trained Model for Natural Language Generation of Indic Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present IndicBART, a multilingual, sequence-to-sequence pre-trained model focusing on 11 Indic languages and English. |
RAJ DABRE et. al. | arxiv-cs.CL | 2021-09-07 |
| 115 | Transformer Models for Text Coherence Assessment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Accordingly, in this paper, we propose four different Transformer-based architectures for the task: vanilla Transformer, hierarchical Transformer, multi-task learning-based model, and a model with fact-based input representation. |
Tushar Abhishek; Daksh Rawat; Manish Gupta; Vasudeva Varma; | arxiv-cs.CL | 2021-09-05 |
| 116 | How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We find that learning to analyse and generate morphologically complex surface representations is still challenging, especially for non-concatenative morphological phenomena like reduplication or vowel harmony and for rare word stems. |
Chantal Amrhein; Rico Sennrich; | arxiv-cs.CL | 2021-09-02 |
| 117 | Masked Adversarial Generation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the Masked Adversarial Generation (MAG) model, that learns to perturb the translation model throughout the training process. |
Badr Youbi Idrissi; Stéphane Clinchant; | arxiv-cs.CL | 2021-09-01 |
| 118 | An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an unsupervised method to build SS corpora from large-scale bilingual translation corpora, alleviating the need for SS supervised corpora. By taking the pair of the source sentences of translation corpus and the translations of their references in a bridge language, we can construct large-scale pseudo parallel SS data. |
Xinyu Lu; Jipeng Qiang; Yun Li; Yunhao Yuan; Yi Zhu; | arxiv-cs.CL | 2021-08-31 |
| 119 | MMARCO: A Multilingual Version of The MS MARCO Passage Ranking Dataset Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present mMARCO, a multilingual version of the MS MARCO passage ranking dataset comprising 13 languages that was created using machine translation. |
LUIZ HENRIQUE BONIFACIO et. al. | arxiv-cs.CL | 2021-08-31 |
| 120 | AraT5: Text-to-Text Transformers for Arabic Language Understanding and Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For evaluation, we use an existing benchmark for Arabic language understanding and introduce a new benchmark for Arabic language generation (ARGEN). |
El Moatez Billah Nagoudi; AbdelRahim Elmadany; Muhammad Abdul-Mageed; | arxiv-cs.CL | 2021-08-30 |
| 121 | Secoco: Self-Correcting Encoding for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents Self-correcting Encoding (Secoco), a framework that effectively deals with input noise for robust neural machine translation by introducing self-correcting predictors. |
TAO WANG et. al. | arxiv-cs.CL | 2021-08-27 |
| 122 | Position-Invariant Truecasing with A Word-and-Character Hierarchical Recurrent Neural Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a fast, accurate and compact two-level hierarchical word-and-character-based recurrent neural network model, the first of its kind for this problem. |
Hao Zhang; You-Chi Cheng; Shankar Kumar; Mingqing Chen; Rajiv Mathews; | arxiv-cs.CL | 2021-08-26 |
| 123 | Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we introduce a method to investigate asymmetrical gender markings. |
Chloe Ciora; Nur Iren; Malihe Alikhani; | arxiv-cs.CL | 2021-08-23 |
| 124 | Recurrent Multiple Shared Layers in Depth for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to train a deeper model with recurrent mechanism, which loops the encoder and decoder blocks of Transformer in the depth direction. |
GuoLiang Li; Yiyang Li; | arxiv-cs.CL | 2021-08-23 |
| 125 | CushLEPOR: Customising HLEPOR Metric Using Optuna for Higher Agreement with Human Judgments or Pre-trained Language Model LaBSE Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we propose to customise traditional metrics by taking advantages of the pre-trained language models (PLMs) and the limited available human labelled scores. |
Lifeng Han; Irina Sorokina; Gleb Erofeev; Serge Gladkoff; | arxiv-cs.CL | 2021-08-21 |
| 126 | Attentive Fine-tuning of Transformers for Translation of Low-resourced Languages @LoResMT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper reports the Machine Translation (MT) systems submitted by the IIITT team for the English->Marathi and English->Irish language pairs LoResMT 2021 shared task. |
KARTHIK PURANIK et. al. | arxiv-cs.CL | 2021-08-19 |
| 127 | Active Learning for Massively Parallel Translation of Constrained Text Into Low Resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an algorithm for human and machine to work together seamlessly to translate a closed text into a severely low resource language. |
Zhong Zhou; Alex Waibel; | arxiv-cs.CL | 2021-08-16 |
| 128 | Findings of The LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the findings of the LoResMT 2021 shared task which focuses on machine translation (MT) of COVID-19 data for both low-resource spoken and sign languages. |
ATUL KR. OJHA et. al. | arxiv-cs.CL | 2021-08-14 |
| 129 | Improving Stylized Neural Machine Translation with Iterative Dual Knowledge Transfer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose an iterative dual knowledge transfer framework that utilizes informal training data of machine translation and formality style transfer data to create large-scale stylized paired data, for the training of stylized machine translation model. |
XUANXUAN WU et. al. | ijcai | 2021-08-13 |
| 130 | M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose the largest dataset for pretraining in Chinese, which consists of over 1.9TB images and 292GB texts. |
JUNYANG LIN et. al. | kdd | 2021-08-12 |
| 131 | Sampling-Based Minimum Bayes Risk Decoding for Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyse this approximation and establish that it has no equivalent to the beam search curse, i.e. better search always leads to better translations. |
Bryan Eikema; Wilker Aziz; | arxiv-cs.CL | 2021-08-10 |
| 132 | Improving Similar Language Translation With Transfer Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work is part of our contribution to the WMT 2021 Similar Languages Translation Shared Task where we submitted models for different language pairs, including French-Bambara, Spanish-Catalan, and Spanish-Portuguese in both directions. |
Ife Adebara; Muhammad Abdul-Mageed; | arxiv-cs.AI | 2021-08-07 |
| 133 | Facebook AI WMT21 News Translation Task Submission Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe Facebook’s multilingual model submission to the WMT2021 shared task on news translation. |
CHAU TRAN et. al. | arxiv-cs.CL | 2021-08-06 |
| 134 | WeChat Neural Machine Translation Systems for WMT21 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces WeChat AI’s participation in WMT 2021 shared news translation task on English->Chinese, English->Japanese, Japanese->English and English->German. |
XIANFENG ZENG et. al. | arxiv-cs.CL | 2021-08-05 |
| 135 | ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective Feedback Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce ChrEnTranslate, an online machine translation demonstration system for translation between English and an endangered language Cherokee. |
Shiyue Zhang; Benjamin Frey; Mohit Bansal; | arxiv-cs.CL | 2021-07-30 |
| 136 | The Cross-Lingual Arabic Information REtrieval (CLAIRE) System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we build our end-to-end Cross-Lingual Arabic Information REtrieval (CLAIRE) system based on the cross-lingual word embedding where searchers are assumed to have a passable passive understanding of Arabic and various supporting information in English is provided to aid retrieval experience. |
Zhizhong Chen; Carsten Eickhoff; | arxiv-cs.IR | 2021-07-29 |
| 137 | Difficulty-Aware Machine Translation Evaluation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel difficulty-aware MT evaluation metric, expanding the evaluation dimension by taking translation difficulty into consideration. |
Runzhe Zhan; Xuebo Liu; Derek F. Wong; Lidia S. Chao; | arxiv-cs.CL | 2021-07-29 |
| 138 | Using Perturbed Length-aware Positional Encoding for Non-autoregressive Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose sequence-level knowledge distillation (SKD) using perturbed length-aware positional encoding and apply it to a student model, the Levenshtein Transformer. |
Yui Oka; Katsuhito Sudoh; Satoshi Nakamura; | arxiv-cs.CL | 2021-07-28 |
| 139 | Cross-lingual Transferring of Pre-trained Contextualized Language Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, building upon the recent works connecting cross-lingual model transferring and neural machine translation, we thus propose a novel cross-lingual model transferring framework for PrLMs: TreLM. |
ZUCHAO LI et. al. | arxiv-cs.CL | 2021-07-27 |
| 140 | On Compositional Generalization of Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study NMT models from the perspective of compositional generalization by building a benchmark dataset, CoGnition, consisting of 216k clean and consistent sentence pairs. |
Yafu Li; Yongjing Yin; Yulong Chen; Yue Zhang; | acl | 2021-07-26 |
| 141 | Towards User-Driven Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To fill this gap, we introduce a novel framework called user-driven NMT. |
HUAN LIN et. al. | acl | 2021-07-26 |
| 142 | Beyond Sentence-Level End-to-End Speech Translation: Context Helps Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate several decoding approaches, and introduce in-model ensemble decoding which jointly performs document- and sentence-level translation using the same model. |
Biao Zhang; Ivan Titov; Barry Haddow; Rico Sennrich; | acl | 2021-07-26 |
| 143 | From Machine Translation to Code-Switching: Generating High-Quality Code-Switched Text Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we adapt a state-of-the-art neural machine translation model to generate Hindi-English code-switched sentences starting from monolingual Hindi sentences. |
Ishan Tarunesh; Syamantak Kumar; Preethi Jyothi; | acl | 2021-07-26 |
| 144 | End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we focus on methods based on training the model with constraints provided as part of the input sequence. |
Josef Jon; Jo?o Paulo Aires; Dusan Varis; Ondrej Bojar; | acl | 2021-07-26 |
| 145 | Revisiting Negation in Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we evaluate the translation of negation both automatically and manually, in English–German (EN–DE) and English–Chinese (EN–ZH). |
Gongbo Tang; Philipp Rönchen; Rico Sennrich; Joakim Nivre; | arxiv-cs.CL | 2021-07-26 |
| 146 | Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel bilingual mutual information (BMI) based adaptive objective, which measures the learning difficulty for each target token from the perspective of bilingualism, and assigns an adaptive weight accordingly to improve token-level adaptive training. |
YANGYIFAN XU et. al. | acl | 2021-07-26 |
| 147 | Don’t Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present a data collection strategy for MT which, in contrast, is cheap and simple, as it does not require bilingual speakers. |
Rajat Bhatnagar; Ananya Ganesh; Katharina Kann; | acl | 2021-07-26 |
| 148 | Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to improve the sampling procedure by selecting the most informative monolingual sentences to complement the parallel data. |
WENXIANG JIAO et. al. | acl | 2021-07-26 |
| 149 | XLPT-AMR: Cross-Lingual Pre-Training Via Multi-Task Learning for Zero-Shot AMR Parsing and Text Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Upon the availability of English AMR dataset and English-to- X parallel datasets, in this paper we propose a novel cross-lingual pre-training approach via multi-task learning (MTL) for both zeroshot AMR parsing and AMR-to-text generation. |
Dongqin Xu; Junhui Li; Muhua Zhu; Min Zhang; Guodong Zhou; | acl | 2021-07-26 |
| 150 | Do Context-Aware Translation Models Pay The Right Attention? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To answer these questions, we introduce SCAT (Supporting Context for Ambiguous Translations), a new English-French dataset comprising supporting context words for 14K translations that professional translators found useful for pronoun disambiguation. |
KAYO YIN et. al. | acl | 2021-07-26 |
| 151 | Rejuvenating Low-Frequency Words: Making The Most of Parallel Data in Non-Autoregressive Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Accordingly, we propose reverse KD to rejuvenate more alignments for low-frequency target words. |
LIANG DING et. al. | acl | 2021-07-26 |
| 152 | Beyond Noise: Mitigating The Impact of Fine-grained Semantic Divergences on Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on these findings, we introduce a divergent-aware NMT framework that uses factors to help NMT recover from the degradation caused by naturally occurring divergences, improving both translation quality and model calibration on EN-FR tasks. |
Eleftheria Briakou; Marine Carpuat; | acl | 2021-07-26 |
| 153 | Point, Disambiguate and Copy: Incorporating Bilingual Dictionaries for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a sophisticated neural architecture to incorporate bilingual dictionaries into Neural Machine Translation (NMT) models. |
TONG ZHANG et. al. | acl | 2021-07-26 |
| 154 | Selective Knowledge Distillation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we design a novel protocol that can effectively analyze the different impacts of samples by comparing various samples’ partitions. |
Fusheng Wang; Jianhao Yan; Fandong Meng; Jie Zhou; | acl | 2021-07-26 |
| 155 | Improving Speech Translation By Understanding and Learning from The Auxiliary Text Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we are interested in training a speech translation model along with an auxiliary text translation task. |
Yun Tang; Juan Pino; Xian Li; Changhan Wang; Dmitriy Genzel; | acl | 2021-07-26 |
| 156 | Mid-Air Hand Gestures for Post-Editing of Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present the first study that investigates the usefulness of mid-air hand gestures in combination with the keyboard (GK) for text editing in PE of MT. Guided by a gesture elicitation study with 14 freelance translators, we develop a prototype supporting mid-air hand gestures for cursor placement, text selection, deletion, and reordering. |
Rashad Albo Jamara; Nico Herbig; Antonio Kr?ger; Josef van Genabith; | acl | 2021-07-26 |
| 157 | Contrastive Learning for Many-to-many Multilingual Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we aim to build a many-to-many translation system with an emphasis on the quality of non-English language directions. |
Xiao Pan; Mingxuan Wang; Liwei Wu; Lei Li; | acl | 2021-07-26 |
| 158 | CCMatrix: Mining Billions of High-Quality Parallel Sentences on The Web IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show that margin-based bitext mining in a multilingual sentence space can be successfully scaled to operate on monolingual corpora of billions of sentences. |
HOLGER SCHWENK et. al. | acl | 2021-07-26 |
| 159 | Good for Misconceived Reasons: An Empirical Revisiting on The Need for Visual Context in Multimodal Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Upon further investigation, we discover that the improvements achieved by the multimodal models over text-only counterparts are in fact results of the regularization effect. |
Zhiyong Wu; Lingpeng Kong; Wei Bi; Xiang Li; Ben Kao; | acl | 2021-07-26 |
| 160 | Prevent The Language Model from Being Overconfident in Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on the property, we propose a Margin-based Token-level Objective (MTO) and a Margin-based Sentence-level Objective (MSO) to maximize the Margin for preventing the LM from being overconfident. |
Mengqi Miao; Fandong Meng; Yijin Liu; Xiao-Hua Zhou; Jie Zhou; | acl | 2021-07-26 |
| 161 | Cross-language Sentence Selection Via Data Augmentation and Rationale Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an approach to cross-language sentence selection in a low-resource setting. |
YANDA CHEN et. al. | acl | 2021-07-26 |
| 162 | Diverse Pretrained Context Encodings Improve Document Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new architecture for adapting a sentence-level sequence-to-sequence transformer by incorporating multiple pre-trained document context signals and assess the impact on translation performance of (1) different pretraining approaches for generating these signals, (2) the quantity of parallel data for which document context is available, and (3) conditioning on source, target, or source and target contexts. |
Domenic Donato; Lei Yu; Chris Dyer; | acl | 2021-07-26 |
| 163 | Modeling Bilingual Conversational Characteristics for Neural Chat Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to promote the translation quality of conversational text by modeling the above properties. |
Yunlong Liang; Fandong Meng; Yufeng Chen; Jinan Xu; Jie Zhou; | acl | 2021-07-26 |
| 164 | Consistency Regularization for Cross-Lingual Fine-Tuning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to improve cross-lingual fine-tuning with consistency regularization. |
BO ZHENG et. al. | acl | 2021-07-26 |
| 165 | Guiding Teacher Forcing with Seer Forcing for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we introduce another decoder, called seer decoder, into the encoder-decoder framework during training, which involves future information in target predictions. |
Yang Feng; Shuhao Gu; Dengji Guo; Zhengxin Yang; Chenze Shao; | acl | 2021-07-26 |
| 166 | The USYD-JD Speech Translation System for IWSLT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the University of Sydney& JD’s joint submission of the IWSLT 2021 low resource speech translation task. |
Liang Ding; Di Wu; Dacheng Tao; | arxiv-cs.CL | 2021-07-24 |
| 167 | Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present an extension of this challenge set, called WiBeMT, with gender-biased adjectives and adds sentences with gender-biased verbs. |
Jonas-Dario Troles; Ute Schmid; | arxiv-cs.CL | 2021-07-24 |
| 168 | Confidence-Aware Scheduled Sampling for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose confidence-aware scheduled sampling. |
Yijin Liu; Fandong Meng; Yufeng Chen; Jinan Xu; Jie Zhou; | arxiv-cs.CL | 2021-07-21 |
| 169 | Integrating Unsupervised Data Generation Into Self-Supervised Neural Machine Translation for Low-Resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, unsupervised machine translation (UMT) exploits large amounts of monolingual data by using synthetic data generation techniques such as back-translation and noising, while self-supervised NMT (SSNMT) identifies parallel sentences in smaller comparable data and trains on them. |
Dana Ruiter; Dietrich Klakow; Josef van Genabith; Cristina España-Bonet; | arxiv-cs.CL | 2021-07-19 |
| 170 | As Easy As 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we develop comprehensive assessments of the robustness of neural machine translation systems to numerical text via behavioural testing. |
JUN WANG et. al. | arxiv-cs.CL | 2021-07-18 |
| 171 | Darmok and Jalad at Tanagra: A Dataset and Model for English-to-Tamarian Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work assembles a Tamarian-English dictionary of utterances from the original episode and several follow-on novels, and uses this to construct a parallel corpus of 456 English-Tamarian utterances. |
Peter Jansen; | arxiv-cs.CL | 2021-07-16 |
| 172 | FST: The FAIR Speech Translation System for The IWSLT21 Multilingual Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe our end-to-end multilingual speech translation system submitted to the IWSLT 2021 evaluation campaign on the Multilingual Speech Translation shared task. |
YUN TANG et. al. | arxiv-cs.CL | 2021-07-14 |
| 173 | DSGPT: Domain-Specific Generative Pre-Training of Transformers for Text Generation in E-commerce Title and Review Summarization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel domain-specific generative pre-training (DSGPT) method for text generation and apply it to the product title and review summarization problems on E-commerce mobile display. |
XUEYING ZHANG et. al. | sigir | 2021-07-13 |
| 174 | The IWSLT 2021 BUT Speech Translation Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study their efficiency from the perspective of having a large amount of separate ASR training data and MT training data, and a smaller amount of speech-translation training data. |
Hari Krishna Vydana; Martin Karafi’at; Luk’as Burget; Honza Cernock’y; | arxiv-cs.CL | 2021-07-13 |
| 175 | Zero-shot Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: These models tend to output the wrong language when performing zero-shot ST. We tackle the issues by including additional training data and an auxiliary loss function that minimizes the text-audio difference. |
Tu Anh Dinh; | arxiv-cs.CL | 2021-07-13 |
| 176 | Putting Words Into The System’s Mouth: A Targeted Attack on Neural Machine Translation Using Monolingual Data Poisoning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present two methods for crafting poisoned examples, and show that only a tiny handful of instances, amounting to only 0.02% of the training set, is sufficient to enact a successful attack. |
JUN WANG et. al. | arxiv-cs.CL | 2021-07-12 |
| 177 | Using Machine Translation to Localize Task Oriented NLG Output Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper explores doing this by applying machine translation to the English output. |
SCOTT ROY et. al. | arxiv-cs.CL | 2021-07-09 |
| 178 | Cross-model Back-translated Distillation for Unsupervised Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel component to the standard UMT framework called Cross-model Back-translated Distillation (CBD), that is aimed to induce another level of data diversification that existing principles lack. |
Xuan-Phi Nguyen; Shafiq Joty; Thanh-Tung Nguyen; Kui Wu; Ai Ti Aw; | icml | 2021-07-08 |
| 179 | Self-supervised and Supervised Joint Training for Resource-rich Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a joint training approach, F2-XEnDec, to combine self-supervised and supervised learning to optimize NMT models. |
Yong Cheng; Wei Wang; Lu Jiang; Wolfgang Macherey; | icml | 2021-07-08 |
| 180 | A Topic Guided Pointer-Generator Model for Generating Natural Language Code Summaries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a neural network model named ToPNN for code summarization, which uses the topics in a broader context (e.g., class) to guide the neural networks that combine the generation of new words and the copy of existing words in code. |
XIN WANG et. al. | arxiv-cs.SE | 2021-07-04 |
| 181 | IITP at WAT 2021: System Description for English-Hindi Multimodal Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We participate in the 8th Workshop on Asian Translation (WAT – 2021) for English-Hindi multimodal translation task and achieve 42.47 and 37.50 BLEU points for Evaluation and Challenge subset, respectively. |
Baban Gain; Dibyanayan Bandyopadhyay; Asif Ekbal; | arxiv-cs.CL | 2021-07-04 |
| 182 | Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the benefit that such compositionality brings about to several machine translation tasks. |
Rahma Chaabouni; Roberto Dessì; Eugene Kharitonov; | arxiv-cs.CL | 2021-07-03 |
| 183 | The USTC-NELSLIP Systems for Simultaneous Speech Translation Task at IWSLT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes USTC-NELSLIP’s submissions to the IWSLT2021 Simultaneous Speech Translation task. |
Dan Liu; Mengge Du; Xiaoxi Li; Yuchen Hu; Lirong Dai; | arxiv-cs.CL | 2021-07-01 |
| 184 | Zero-pronoun Data Augmentation for Japanese-to-English Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a data augmentation method that provides additional training signals for the translation model to learn correlations between local context and zero pronouns. |
Ryokan Ri; Toshiaki Nakazawa; Yoshimasa Tsuruoka; | arxiv-cs.CL | 2021-07-01 |
| 185 | Modeling Target-side Inflection in Placeholder Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose a novel method of placeholder translation that can inflect specified terms according to the grammatical construction of the output sentence. |
Ryokan Ri; Toshiaki Nakazawa; Yoshimasa Tsuruoka; | arxiv-cs.CL | 2021-07-01 |
| 186 | IMS’ Systems for The IWSLT 2021 Low-Resource Speech Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team. |
Pavel Denisov; Manuel Mager; Ngoc Thang Vu; | arxiv-cs.CL | 2021-06-30 |
| 187 | Rethinking The Evaluation of Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel evaluation protocol, which not only avoids the effect of search errors but provides a system-level evaluation in the perspective of model ranking. |
Jianhao Yan; Chenming Wu; Fandong Meng; Jie Zhou; | arxiv-cs.CL | 2021-06-29 |
| 188 | DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation By Augmenting Pretrained Multilingual Encoders Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To reduce this gap, we introduce DeltaLM, a pretrained multilingual encoder-decoder model that regards the decoder as the task layer of off-the-shelf pretrained encoders. |
SHUMING MA et. al. | arxiv-cs.CL | 2021-06-25 |
| 189 | On The Influence of Machine Translation on Language Origin Obfuscation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we analyze the ability to detect the source language from the translated output of two widely used commercial machine translation systems by utilizing machine-learning algorithms with basic textual features like n-grams. |
Benjamin Murauer; Michael Tschuggnall; Günther Specht; | arxiv-cs.CL | 2021-06-24 |
| 190 | End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we focus on methods based on training the model with constraints provided as part of the input sequence. |
Josef Jon; João Paulo Aires; Dušan Variš; Ondřej Bojar; | arxiv-cs.CL | 2021-06-23 |
| 191 | Dealing with Training and Test Segmentation Mismatch: FBK@IWSLT2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes FBK’s system submission to the IWSLT 2021 Offline Speech Translation task. |
Sara Papi; Marco Gaido; Matteo Negri; Marco Turchi; | arxiv-cs.CL | 2021-06-23 |
| 192 | Phrase-level Active Learning for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address this problem in an active learning setting where we can spend a given budget on translating in-domain data, and gradually fine-tune a pre-trained out-of-domain NMT model on the newly translated data. |
Junjie Hu; Graham Neubig; | arxiv-cs.CL | 2021-06-21 |
| 193 | Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to share parameters across all layers thereby leading to a recurrently stacked neural network model. |
Raj Dabre; Atsushi Fujita; | arxiv-cs.CL | 2021-06-18 |
| 194 | Lost in Interpreting: Speech Translation from Source or Interpreter? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate if such an automatic system should rather follow the original speaker, or an interpreter to achieve better translation quality at the cost of increased delay. |
Dominik Macháček; Matúš Žilinec; Ondřej Bojar; | arxiv-cs.CL | 2021-06-17 |
| 195 | Central Kurdish Machine Translation: First Large Scale Parallel Corpus and Experiments Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first large scale parallel corpus of Central Kurdish-English, Awta, containing 229,222 pairs of manually aligned translations. |
Zhila Amini; Mohammad Mohammadamini; Hawre Hosseini; Mehran Mansouri; Daban Jaff; | arxiv-cs.AI | 2021-06-17 |
| 196 | Evaluating Gender Bias in Hindi-English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We implement a modified version of the existing TGBI metric based on the grammatical considerations for Hindi. |
Gauri Gupta; Krithika Ramesh; Sanjay Singh; | arxiv-cs.CL | 2021-06-16 |
| 197 | Alternated Training with Synthetic and Authentic Data for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose alternated training with synthetic and authentic data for NMT. Compared with previous work, we introduce authentic data as guidance to prevent the training of NMT models from being disturbed by noisy synthetic data. |
Rui Jiao; Zonghan Yang; Maosong Sun; Yang Liu; | arxiv-cs.CL | 2021-06-16 |
| 198 | English to Bangla Machine Translation Using Recurrent Neural Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes an architecture of English to Bangla machine translation system. |
Shaykh Siddique; Tahmid Ahmed; Md. Rifayet Azam Talukder; Md. Mohsin Uddin; | arxiv-cs.CL | 2021-06-14 |
| 199 | Machine Translation Into Low-resource Language Varieties Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a general framework to rapidly adapt MT systems to generate language varieties that are close to, but different from, the standard target language, using no parallel (source–variety) data. |
Sachin Kumar; Antonios Anastasopoulos; Shuly Wintner; Yulia Tsvetkov; | arxiv-cs.CL | 2021-06-12 |
| 200 | Predicting The Ordering of Characters in Japanese Historical Documents Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We explore a few approaches to the task of predicting the sequential ordering of the characters: one using simple hand-crafted rules, another using hand-crafted rules with adaptive thresholds, and another using a deep recurrent sequence model trained with teacher forcing. |
Alex Lamb; Tarin Clanuwat; Siyu Han; Mikel Bober-Irizar; Asanobu Kitamoto; | arxiv-cs.CL | 2021-06-12 |
| 201 | UC2: Universal Cross-Lingual Cross-Modal Vision-and-Language Pre-Training IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To generalize this success to non-English languages, we introduce UC^2, the first machine translation-augmented framework for cross-lingual cross-modal representation learning. |
MINGYANG ZHOU et. al. | cvpr | 2021-06-11 |
| 202 | Exploring Unsupervised Pretraining Objectives for Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we systematically compare masking with alternative objectives that produce inputs resembling real (full) sentences, by reordering and replacing words based on their context. |
Christos Baziotis; Ivan Titov; Alexandra Birch; Barry Haddow; | arxiv-cs.CL | 2021-06-10 |
| 203 | Crosslingual Embeddings Are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that initializing the embedding layer of UNMT models with cross-lingual embeddings shows significant improvements in BLEU score over existing approaches with embeddings randomly initialized. |
Tamali Banerjee; Rudra Murthy V; Pushpak Bhattacharyya; | arxiv-cs.CL | 2021-06-09 |
| 204 | Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our systems that were submitted to the restricted translation task at WAT 2021. |
Katsuki Chousa; Makoto Morishita; | arxiv-cs.CL | 2021-06-09 |
| 205 | Multilingual Neural Semantic Parsing for Low-Resourced Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the data limitation problem, we propose using machine translation to bootstrap multilingual training data from the more abundant English data. To evaluate our multilingual models on human-written sentences as opposed to machine translated ones, we introduce a new multilingual semantic parsing dataset in English, Italian and Japanese based on the Facebook Task Oriented Parsing (TOP) dataset. |
Menglin Xia; Emilio Monti; | arxiv-cs.CL | 2021-06-07 |
| 206 | The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce the FLORES-101 evaluation benchmark, consisting of 3001 sentences extracted from English Wikipedia and covering a variety of different topics and domains. |
NAMAN GOYAL et. al. | arxiv-cs.CL | 2021-06-06 |
| 207 | Cross-language Sentence Selection Via Data Augmentation and Rationale Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an approach to cross-language sentence selection in a low-resource setting. |
YANDA CHEN et. al. | arxiv-cs.CL | 2021-06-04 |
| 208 | Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to improve the sampling procedure by selecting the most informative monolingual sentences to complement the parallel data. |
WENXIANG JIAO et. al. | arxiv-cs.CL | 2021-06-02 |
| 209 | Part of Speech and Universal Dependency Effects on English Arabic Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this research paper, I will elaborate on a method to evaluate machine translation models based on their performance on underlying syntactical phenomena between English and Arabic languages. |
Ofek Rafaeli; Omri Abend; Leshem Choshen; Dmitry Nikolaev; | arxiv-cs.CL | 2021-06-01 |
| 210 | ViTA: Visual-Linguistic Translation By Aligning Object Tags Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose our system under the team name Volta for the Multimodal Translation Task of WAT 2021 from English to Hindi. |
Kshitij Gupta; Devansh Gautam; Radhika Mamidi; | arxiv-cs.CL | 2021-06-01 |
| 211 | Bangla Natural Language Processing: A Comprehensive Review of Classical, Machine Learning, and Deep Learning Based Methods Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we present a thorough review of 71 BNLP research papers and categorize them into 11 categories, namely Information Extraction, Machine Translation, Named Entity Recognition, Parsing, Parts of Speech Tagging, Question Answering System, Sentiment Analysis, Spam and Fake Detection, Text Summarization, Word Sense Disambiguation, and Speech Processing and Recognition. |
OVISHAKE SEN et. al. | arxiv-cs.CL | 2021-05-31 |
| 212 | Multilingual Speech Translation with Unified Transformer: Huawei Noah’s Ark Lab at IWSLT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the system submitted to the IWSLT 2021 Multilingual Speech Translation (MultiST) task from Huawei Noah’s Ark Lab. |
Xingshan Zeng; Liangyou Li; Qun Liu; | arxiv-cs.CL | 2021-05-31 |
| 213 | Korean-English Machine Translation with Multiple Tokenization Strategy Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, alphabet tokenization, morpheme tokenization, and BPE tokenization were applied to Korean as the source language and English as the target language respectively, and the comparison experiment was conducted by repeating 50,000 epochs of each 9 models using the Transformer neural network. |
Dojun Park; Youngjin Jang; Harksoo Kim; | arxiv-cs.CL | 2021-05-29 |
| 214 | Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop models under different conditions, employing both (i) standard end-to-end sequence-to-sequence (S2S) Transformers trained from scratch and (ii) pre-trained S2S language models (LMs). |
El Moatez Billah Nagoudi; AbdelRahim Elmadany; Muhammad Abdul-Mageed; | arxiv-cs.LG | 2021-05-27 |
| 215 | How Does Distilled Data Complexity Impact The Quality and Confidence of Non-Autoregressive Machine Translation? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we seek to understand why distillation is so effective. |
Weijia Xu; Shuming Ma; Dongdong Zhang; Marine Carpuat; | arxiv-cs.CL | 2021-05-26 |
| 216 | IntelliCAT: Intelligent Machine Translation Post-Editing with Quality Estimation and Translation Suggestion Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present IntelliCAT, an interactive translation interface with neural models that streamline the post-editing process on machine translation output. |
Dongjun Lee; Junhyeong Ahn; Heesoo Park; Jaemin Jo; | arxiv-cs.CL | 2021-05-25 |
| 217 | Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on sequence-level knowledge distillation (SeqKD) from external text-based NMT models. |
Hirofumi Inaguma; Tatsuya Kawahara; Shinji Watanabe; | naacl | 2021-05-23 |
| 218 | MT5: A Massively Multilingual Pre-trained Text-to-Text Transformer IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages. |
LINTING XUE et. al. | naacl | 2021-05-23 |
| 219 | Neural Machine Translation Without Embeddings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Surprisingly, replacing the ubiquitous embedding layer with one-hot representations of each byte does not hurt performance; experiments on byte-to-byte machine translation from English to 10 different languages show a consistent improvement in BLEU, rivaling character-level and even standard subword-level models. |
Uri Shaham; Omer Levy; | naacl | 2021-05-23 |
| 220 | Unsupervised Vision-and-Language Pre-training Without Parallel Images and Captions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we propose to conduct mask-and-predict pre-training on text-only and image-only corpora and introduce the object tags detected by an object recognition model as anchor points to bridge two modalities. |
LIUNIAN HAROLD LI et. al. | naacl | 2021-05-23 |
| 221 | What�s in A Summary? Laying The Groundwork for Advances in Hospital-Course Summarization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we introduce the task of hospital-course summarization. |
Griffin Adams; Emily Alsentzer; Mert Ketenci; Jason Zucker; No�mie Elhadad; | naacl | 2021-05-23 |
| 222 | Cross-lingual Cross-modal Pretraining for Multimodal Retrieval Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a new approach to learn cross-lingual cross-modal representations for matching images and their relevant captions in multiple languages. |
Hongliang Fei; Tan Yu; Ping Li; | naacl | 2021-05-23 |
| 223 | SGL: Speaking The Graph Languages of Semantic Parsing Via Multilingual Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, instead, we reframe semantic parsing towards multiple formalisms as Multilingual Neural Machine Translation (MNMT), and propose SGL, a many-to-many seq2seq architecture trained with an MNMT objective. |
Luigi Procopio; Rocco Tripodi; Roberto Navigli; | naacl | 2021-05-23 |
| 224 | Generative Imagination Elevates Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose ImagiT, a novel machine translation method via visual imagination. |
Quanyu Long; Mingxuan Wang; Lei Li; | naacl | 2021-05-23 |
| 225 | Non-Autoregressive Translation By Learning Target Categorical Codes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose CNAT, which learns implicitly categorical codes as latent variables into the non-autoregressive decoding. |
YU BAO et. al. | naacl | 2021-05-23 |
| 226 | Training Data Augmentation for Code-Mixed Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an m-BERT based procedure whose core learnable component is a ternary sequence labeling model, that can be trained with a limited code-mixed corpus alone. |
Abhirut Gupta; Aditya Vavre; Sunita Sarawagi; | naacl | 2021-05-23 |
| 227 | Counterfactual Data Augmentation for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a data augmentation method for neural machine translation. |
Qi Liu; Matt Kusner; Phil Blunsom; | naacl | 2021-05-23 |
| 228 | Harnessing Multilinguality in Unsupervised Machine Translation for Rare Languages IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that multilinguality is critical to making unsupervised systems practical for low-resource settings. |
Xavier Garcia; Aditya Siddhant; Orhan Firat; Ankur Parikh; | naacl | 2021-05-23 |
| 229 | Searchable Hidden Intermediates for End-to-End Models of Decomposable Sequence Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present an end-to-end framework that exploits compositionality to learn searchable hidden representations at intermediate stages of a sequence model using decomposed sub-tasks. |
Siddharth Dalmia; Brian Yan; Vikas Raunak; Florian Metze; Shinji Watanabe; | naacl | 2021-05-23 |
| 230 | On Learning Text Style Transfer with Direct Rewards Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore training algorithms that instead optimize reward functions that explicitly consider different aspects of the style-transferred outputs. |
Yixin Liu; Graham Neubig; John Wieting; | naacl | 2021-05-23 |
| 231 | UniDrop: A Simple Yet Effective Technique to Improve Transformer Without Extra Cost Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we integrate different dropout techniques into the training of Transformer models. |
ZHEN WU et. al. | naacl | 2021-05-23 |
| 232 | Backtranslation Feedback Improves User Confidence in MT, Not Quality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Translating text into a language unknown to the text’s author, dubbed outbound translation, is a modern need for which the user experience has significant room for improvement, beyond the basic machine translation facility. We demonstrate this by showing three ways in which user confidence in the outbound translation, as well as its overall final quality, can be affected: backward translation, quality estimation (with alignment) and source paraphrasing. |
VIL�M ZOUHAR et. al. | naacl | 2021-05-23 |
| 233 | From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the challenge, we propose a joint learning approach, with English SLU training data and non-English auxiliary tasks from raw text, syntax and translation for transfer. |
ROB VAN DER GOOT et. al. | naacl | 2021-05-23 |
| 234 | XOR QA: Cross-lingual Open-Retrieval Question Answering IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this dataset, we introduce a task framework, called Cross-lingual Open-Retrieval Question Answering (XOR QA), that consists of three new tasks involving cross-lingual document retrieval from multilingual and English resources. |
AKARI ASAI et. al. | naacl | 2021-05-23 |
| 235 | Investigating Math Word Problems Using Pretrained Multilingual Language Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we revisit math word problems~(MWPs) from the cross-lingual and multilingual perspective. |
Minghuan Tan; Lei Wang; Lingxiao Jiang; Jing Jiang; | arxiv-cs.CL | 2021-05-19 |
| 236 | Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe models focused at the understudied problem of translating between monolingual and code-mixed language pairs. |
Ganesh Jawahar; El Moatez Billah Nagoudi; Muhammad Abdul-Mageed; Laks V. S. Lakshmanan; | arxiv-cs.CL | 2021-05-18 |
| 237 | Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a model to resolve the heterogeneity in the sequence to sequence task. |
Yunhao Yang; Zhaokun Xue; | arxiv-cs.CL | 2021-05-18 |
| 238 | Ensemble-based Transfer Learning for Low-resource Machine Translation Quality Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the Sentence-Level QE Shared Task of the Fifth Conference on Machine Translation (WMT20), but in a more challenging setting. |
Ting-Wei Wu; Yung-An Hsieh; Yi-Chieh Liu; | arxiv-cs.CL | 2021-05-17 |
| 239 | A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a general multi-task learning framework to leverage text data for ASR and ST tasks. |
Y. Tang; J. Pino; C. Wang; X. Ma; D. Genzel; | icassp | 2021-05-16 |
| 240 | Modeling Homophone Noise for Robust Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a robust neural machine translation (NMT) framework to deal with homophone errors. |
W. QIN et. al. | icassp | 2021-05-16 |
| 241 | An Empirical Study on Task-Oriented Dialogue Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we systematically investigate advanced models on the task-oriented dialogue translation task, including sentence-level, document-level and non-autoregressive NMT models. |
S. Liu; | icassp | 2021-05-16 |
| 242 | Data Augmentation for Sign Language Gloss Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We focus here on gloss-to-text translation, which we treat as a low-resource neural machine translation (NMT) problem. |
Amit Moryossef; Kayo Yin; Graham Neubig; Yoav Goldberg; | arxiv-cs.CL | 2021-05-16 |
| 243 | Cascaded Models with Cyclic Feedback for Direct Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a technique that allows cascades of automatic speech recognition (ASR) and machine translation (MT) to exploit in-domain direct speech translation data in addition to out-of-domain MT and ASR data. |
T. K. Lam; S. Schamoni; S. Riezler; | icassp | 2021-05-16 |
| 244 | Machine Translation Verbosity Control for Automatic Dubbing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the problem of controlling the verbosity of machine translation out-put, so that subsequent steps of our automatic dubbing pipeline can generate dubs of better quality. |
S. M. Lakew; et al. | icassp | 2021-05-16 |
| 245 | Task Aware Multi-Task Learning for Speech to Text Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a task modulation network which allows the model to learn task specific features, while learning the shared features simultaneously. |
S. Indurthi; et al. | icassp | 2021-05-16 |
| 246 | Jointly Trained Transformers Models for Spoken Language Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, degradation in performance is reduced by creating an End-to-End differentiable pipeline between the ASR and MT systems. |
H. K. Vydana; M. Karafi�t; K. Zmolikova; L. Burget; H. Cernock�; | icassp | 2021-05-16 |
| 247 | From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the challenge, we propose a joint learning approach, with English SLU training data and non-English auxiliary tasks from raw text, syntax and translation for transfer. |
ROB VAN DER GOOT et. al. | arxiv-cs.CL | 2021-05-15 |
| 248 | The Volctrans Neural Speech Translation System for IWSLT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the systems submitted to IWSLT 2021 by the Volctrans team. |
CHENGQI ZHAO et. al. | arxiv-cs.CL | 2021-05-15 |
| 249 | Do Context-Aware Translation Models Pay The Right Attention? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we ask several questions: What contexts do human translators use to resolve ambiguous words? |
KAYO YIN et. al. | arxiv-cs.CL | 2021-05-14 |
| 250 | Dynamic Multi-Branch Layers for On-Device Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by conditional computation, we propose to improve the performance of on-device NMT systems with dynamic multi-branch layers. |
Zhixing Tan; Maosong Sun; Yang Liu; | arxiv-cs.CL | 2021-05-14 |
| 251 | Self-Guided Curriculum Learning for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this, we propose a self-guided curriculum strategy to encourage the learning of neural machine translation (NMT) models to follow the above recovery criterion, where we cast the recovery degree of each training example as its learning difficulty. |
LEI ZHOU et. al. | arxiv-cs.CL | 2021-05-10 |
| 252 | Automatic Classification of Human Translation and Machine Translation: A Study from The Perspective of Lexical Diversity Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: By using a trigram model and fine-tuning a pretrained BERT model for sequence classification, we show that machine translation and human translation can be classified with an accuracy above chance level, which suggests that machine translation and human translation are different in a systematic way. |
Yingxue Fu; Mark-Jan Nederhof; | arxiv-cs.CL | 2021-05-10 |
| 253 | End-to-End Speech Translation with Pre-trained Models and Adapters: UPC at IWSLT 2021 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the submission to the IWSLT 2021 offline speech translation task by the UPC Machine Translation group. |
Gerard I. Gállego; Ioannis Tsiamas; Carlos Escolano; José A. R. Fonollosa; Marta R. Costa-jussà; | arxiv-cs.CL | 2021-05-10 |
| 254 | Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a continual pre-training (CPT) framework on mBART to effectively adapt it to unseen languages. |
Zihan Liu; Genta Indra Winata; Pascale Fung; | arxiv-cs.CL | 2021-05-09 |
| 255 | Learning Shared Semantic Space for Speech-to-Text Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In observation of this obstacle, we propose to bridge this representation gap with Chimera. |
Chi Han; Mingxuan Wang; Heng Ji; Lei Li; | arxiv-cs.CL | 2021-05-07 |
| 256 | Duplex Sequence-to-Sequence Learning for Reversible Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a {\em duplex} seq2seq neural network, REDER (Reversible Duplex Transformer), and apply it to machine translation. |
ZAIXIANG ZHENG et. al. | arxiv-cs.CL | 2021-05-07 |
| 257 | Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper investigates two key aspects of end-to-end simultaneous speech translation: (a) how to encode efficiently the continuous speech flow, and (b) how to segment the speech flow in order to alternate optimally between reading (R: encoding input) and writing (W: decoding output) operations. |
Ha Nguyen; Yannick Estève; Laurent Besacier; | arxiv-cs.CL | 2021-04-29 |
| 258 | End-to-end Speech Translation Via Cross-modal Progressive Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Cross Speech-Text Network (XSTNet), an end-to-end model for speech-to-text translation. |
Rong Ye; Mingxuan Wang; Lei Li; | arxiv-cs.CL | 2021-04-21 |
| 259 | Should We Stop Training More Monolingual Models, and Simply Use Machine Translation Instead? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Most work in NLP makes the assumption that it is desirable to develop solutions in the native language in question. |
Tim Isbister; Fredrik Carlsson; Magnus Sahlgren; | arxiv-cs.CL | 2021-04-21 |
| 260 | Addressing The Vulnerability of NMT in Input Perturbations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we improve the robustness of NMT models by reducing the effect of noisy words through a Context-Enhanced Reconstruction (CER) approach. |
Weiwen Xu; Ai Ti Aw; Yang Ding; Kui Wu; Shafiq Joty; | arxiv-cs.CL | 2021-04-20 |
| 261 | Grammatical Error Generation Based on Translated Fragments Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our method aims at simulating mistakes made by second language learners, and produces a wider range of non-native style language in comparison to state-of-the-art synthetic data creation methods. |
Eetu Sjöblom; Mathias Creutz; Teemu Vahtola; | arxiv-cs.CL | 2021-04-20 |
| 262 | Documenting Large Webtext Corpora: A Case Study on The Colossal Clean Crawled Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we provide some of the first documentation for the Colossal Clean Crawled Corpus (C4; Raffel et al., 2020), a dataset created by applying a set of filters to a single snapshot of Common Crawl. |
JESSE DODGE et. al. | arxiv-cs.CL | 2021-04-18 |
| 263 | DCH-2: A Parallel Customer-Helpdesk Dialogue Corpus with Distributions of Annotators’ Labels Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a data set called DCH-2, which contains 4,390 real customer-helpdesk dialogues in Chinese and their English translations. |
Zhaohao Zeng; Tetsuya Sakai; | arxiv-cs.CL | 2021-04-18 |
| 264 | Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained Encoders Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on a zero-shot cross-lingual transfer task in NMT. |
GUANHUA CHEN et. al. | arxiv-cs.CL | 2021-04-18 |
| 265 | Stream-level Latency Evaluation for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a stream-level adaptation of the current latency measures based on a re-segmentation approach applied to the output translation, that is successfully evaluated on streaming conditions for a reference IWSLT task. |
Javier Iranzo-Sánchez; Jorge Civera; Alfons Juan; | arxiv-cs.CL | 2021-04-18 |
| 266 | MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we improve multilingual text-to-text transfer Transformer with translation pairs (mT6). |
ZEWEN CHI et. al. | arxiv-cs.CL | 2021-04-17 |
| 267 | Improving Neural Machine Translation with Compact Word Embedding Tables Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we analyze the impact and utility of such matrices in the context of neural machine translation (NMT). |
Krtin Kumar; Mehdi Rezagholizadeh; Yiu Sing Lau; Qun Liu; | arxiv-cs.CL | 2021-04-17 |
| 268 | XLEnt: Mining A Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we propose Lexical-Semantic-Phonetic Align (LSP-Align), a technique to automatically mine cross-lingual entity lexica from mined web data. |
Ahmed El-Kishky; Adithya Renduchintala; James Cross; Francisco Guzmán; Philipp Koehn; | arxiv-cs.CL | 2021-04-17 |
| 269 | Sentence Alignment with Parallel Documents Helps Biomedical Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a new unsupervised sentence alignment method and explores features in training biomedical neural machine translation (NMT) systems. |
Shengxuan Luo; Huaiyuan Ying; Sheng Yu; | arxiv-cs.CL | 2021-04-17 |
| 270 | Crossing The Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work provides an extensive overview of existing methods and resources in multilingual ToD as an entry point to this exciting and emerging field. |
EVGENIIA RAZUMOVSKAIA et. al. | arxiv-cs.CL | 2021-04-17 |
| 271 | Towards Variable-Length Textual Adversarial Attacks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose variable-length textual adversarial attacks~(VL-Attack) and integrate three atomic operations, namely \textit{insertion}, \textit{deletion} and \textit{replacement}, into a unified framework, by introducing and manipulating a special \textit{blank} token while attacking. |
JUNLIANG GUO et. al. | arxiv-cs.CL | 2021-04-16 |
| 272 | Robust Open-Vocabulary Translation from Visual Text Representations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the robustness of human language processing, we propose the use of visual text representations, which dispense with a finite set of text embeddings in favor of continuous vocabularies created by processing visually rendered text with sliding windows. |
Elizabeth Salesky; David Etter; Matt Post; | arxiv-cs.CL | 2021-04-16 |
| 273 | Simultaneous Multi-Pivot Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve this issue, we propose multi-pivot translation and apply it to a simultaneous translation setting involving pivot languages. |
Raj Dabre; Aizhan Imankulova; Masahiro Kaneko; Abhisek Chakrabarty; | arxiv-cs.CL | 2021-04-15 |
| 274 | Investigating Failures of Automatic Translation in The Case of Unambiguous Gender Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We find that even when the surrounding context provides unambiguous evidence of the appropriate grammatical gender marking, no transformer based model we tested was able to accurately gender occupation nouns systematically. We release an evaluation scheme and dataset for measuring the ability of transformer based NMT models to translate gender morphology correctly in unambiguous contexts across syntactically diverse sentences. |
Adithya Renduchintala; Adina Williams; | arxiv-cs.CL | 2021-04-15 |
| 275 | Hierarchical Learning for Generation with Long Source Sequences Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design and study a new Hierarchical Attention Transformer-based architecture (HAT) that outperforms standard Transformers on several sequence to sequence tasks. |
Tobias Rohde; Xiaoxia Wu; Yinhan Liu; | arxiv-cs.CL | 2021-04-15 |
| 276 | Zero-Shot Cross-lingual Semantic Parsing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a multi-task encoder-decoder model to transfer parsing knowledge to additional languages using only English-Logical form paired data and unlabeled, monolingual utterances in each test language. |
Tom Sherborne; Mirella Lapata; | arxiv-cs.CL | 2021-04-15 |
| 277 | Improving Gender Translation Accuracy with Filtered Self-Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a gender-filtered self-training technique to improve gender translation accuracy on unambiguously gendered inputs. |
Prafulla Kumar Choubey; Anna Currey; Prashant Mathur; Georgiana Dinu; | arxiv-cs.CL | 2021-04-15 |
| 278 | I Wish I Would Have Loved This One, But I Didn’t — A Multilingual Dataset for Counterfactual Detection in Product Reviews Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider the problem of counterfactual detection (CFD) in product reviews. For this purpose, we annotate a multilingual CFD dataset from Amazon product reviews covering counterfactual statements written in English, German, and Japanese languages. |
James O’Neill; Polina Rozenshtein; Ryuichi Kiryo; Motoko Kubota; Danushka Bollegala; | arxiv-cs.CL | 2021-04-14 |
| 279 | Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: The development of deep learning techniques has allowed Neural Machine Translation (NMT) models to become extremely powerful, given sufficient training data and training time. … |
Danielle Saunders; | arxiv-cs.CL | 2021-04-14 |
| 280 | Family of Origin and Family of Choice: Massively Parallel Lexiconized Iterative Pretraining for Severely Low Resource Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To translate named entities correctly, we build a massive lexicon table for 2,939 Bible named entities in 124 source languages, and include many that occur once and covers more than 66 severely low resource languages. |
Zhong Zhou; Alex Waibel; | arxiv-cs.CL | 2021-04-12 |
| 281 | Backtranslation Feedback Improves User Confidence in MT, Not Quality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe an experiment on outbound translation from English to Czech and Estonian. |
VILÉM ZOUHAR et. al. | arxiv-cs.CL | 2021-04-12 |
| 282 | Sentiment-based Candidate Selection for NMT Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Grounded in the observation that UGC features highly idiomatic, sentiment-charged language, we propose a decoder-side approach that incorporates automatic sentiment scoring into the MT candidate selection process. |
Alex Jones; Derry Tanti Wijaya; | arxiv-cs.CL | 2021-04-10 |
| 283 | Extended Parallel Corpus for Amharic-English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the acquisition, preprocessing, segmentation, and alignment of an Amharic-English parallel corpus. |
Andargachew Mekonnen Gezmu; Andreas Nürnberger; Tesfaye Bayu Bati; | arxiv-cs.CL | 2021-04-08 |
| 284 | Design and Implementation of English To Yoruba Verb Phrase Machine Translation System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We aim to develop an English to Yoruba machine translation system which can translate English verb phrase text to its Yoruba equivalent.Words from both languages Source Language and Target Language were collected for the verb phrase group in the home domain.The lexical translation is done by assigning values of the matching word in the dictionary.The syntax of the two languages was realized using Context-Free Grammar,we validated the rewrite rules with finite state automata.The human evaluation method was used and expert fluency scored.The evaluation shows the system performed better than that of sampled Google translation with over 70 percent of the response matching that of the system’s output. |
Safiriyu Eludiora; Benjamin Ajibade; | arxiv-cs.CL | 2021-04-08 |
| 285 | Interpreting Verbal Metaphors By Paraphrasing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we interpret metaphors with BERT and WordNet hypernyms and synonyms in an unsupervised manner, showing that our method significantly outperforms the state-of-the-art baseline. |
Rui Mao; Chenghua Lin; Frank Guerin; | arxiv-cs.CL | 2021-04-07 |
| 286 | AI4D — African Language Program Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work details the AI4D – African Language Program, a 3-part project that 1) incentivised the crowd-sourcing, collection and curation of language datasets through an online quantitative and qualitative challenge, 2) supported research fellows for a period of 3-4 months to create datasets annotated for NLP tasks, and 3) hosted competitive Machine Learning challenges on the basis of these datasets. |
KATHLEEN SIMINYU et. al. | arxiv-cs.CL | 2021-04-06 |
| 287 | IndT5: A Text-to-Text Transformer for 10 Indigenous Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce IndT5, the first Transformer language model for Indigenous languages. |
El Moatez Billah Nagoudi; Wei-Rui Chen; Muhammad Abdul-Mageed; Hasan Cavusogl; | arxiv-cs.CL | 2021-04-04 |
| 288 | Low-Resource Neural Machine Translation for Southern African Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this challenge we compare zero-shot learning, transfer learning and multilingual learning on three Bantu languages (Shona, isiXhosa and isiZulu) and English. |
Evander Nyoni; Bruce A. Bassett; | arxiv-cs.CL | 2021-04-01 |
| 289 | Many-to-English Machine Translation Tools, Data, and Pretrained Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present useful tools for machine translation research: MTData, NLCodec, and RTG. |
Thamme Gowda; Zhao Zhang; Chris A Mattmann; Jonathan May; | arxiv-cs.CL | 2021-04-01 |
| 290 | Sampling and Filtering of Neural Machine Translation Distillation Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The highest-scoring hypothesis of the teacher model is commonly used to train a new model (student). |
Vilém Zouhar; | arxiv-cs.CL | 2021-04-01 |
| 291 | Autocorrect in The Process of Translation — Multi-task Learning Improves Dialogue Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we conduct a deep analysis of a dialogue corpus and summarize three major issues on dialogue translation, including pronoun dropping (\droppro), punctuation dropping (\droppun), and typos (\typo). To properly evaluate the performance, we propose a manually annotated dataset with 1,931 Chinese-English parallel utterances from 300 dialogues as a benchmark testbed for dialogue translation. |
Tao Wang; Chengqi Zhao; Mingxuan Wang; Lei Li; Deyi Xiong; | arxiv-cs.CL | 2021-03-30 |
| 292 | An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a case study of Tigrinya where we investigate several back-translation methods to generate synthetic source sentences. |
Lidia Kidane; Sachin Kumar; Yulia Tsvetkov; | arxiv-cs.CL | 2021-03-30 |
| 293 | English-Twi Parallel Corpus for Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a parallel machine translation training corpus for English and Akuapem Twi of 25,421 sentence pairs. |
PAUL AZUNRE et. al. | arxiv-cs.CL | 2021-03-29 |
| 294 | Contextual Text Embeddings for Twi Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The specific contribution of this research work is the development of several pretrained transformer language models for the Akuapem and Asante dialects of Twi, paving the way for advances in application areas such as Named Entity Recognition (NER), Neural Machine Translation (NMT), Sentiment Analysis (SA) and Part-of-Speech (POS) tagging. |
PAUL AZUNRE et. al. | arxiv-cs.CL | 2021-03-29 |
| 295 | Unsupervised Machine Translation On Dravidian Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on unsupervised translation between English and Kannada, a low resource Dravidian language. |
Sai Koneru; Danni Liu; Jan Niehues; | arxiv-cs.CL | 2021-03-29 |
| 296 | PENELOPIE: Enabling Open Information Extraction for The Greek Language Through Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present our submission for the EACL 2021 SRW; a methodology that aims at bridging the gap between high and low-resource languages in the context of Open Information Extraction, showcasing it on the Greek language. |
Dimitris Papadopoulos; Nikolaos Papadakis; Nikolaos Matsatsinis; | arxiv-cs.CL | 2021-03-28 |
| 297 | Low-Resource Machine Translation Training Curriculum Fit for Low-Resource Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We conduct an empirical study of neural machine translation (NMT) for truly low-resource languages, and propose a training curriculum fit for cases when both parallel training data and compute resource are lacking, reflecting the reality of most of the world’s languages and the researchers working on these languages. |
GARRY KUWANTO et. al. | arxiv-cs.CL | 2021-03-24 |
| 298 | Repairing Pronouns in Translation with BERT-Based Post-Editing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the severity of this pronoun issue, showing that (1) in some domains, pronoun choice can account for more than half of a NMT systems’ errors, and (2) pronouns have a disproportionately large impact on perceived translation quality. |
Reid Pryzant; | arxiv-cs.CL | 2021-03-23 |
| 299 | The Effectiveness of Morphology-aware Segmentation in Low-Resource Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper evaluates the performance of several modern subword segmentation methods in a low-resource neural machine translation setting. |
Jonne Sälevä; Constantine Lignos; | arxiv-cs.CL | 2021-03-20 |
| 300 | Dependency Graph-to-String Statistical Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present graph-based translation models which translate source graphs into target strings. |
Liangyou Li; Andy Way; Qun Liu; | arxiv-cs.CL | 2021-03-20 |
| 301 | Congolese Swahili Machine Translation for Humanitarian Response Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we describe our efforts to make a bidirectional Congolese Swahili (SWC) to French (FRA) neural machine translation system with the motivation of improving humanitarian translation workflows. For training, we created a 25,302-sentence general domain parallel corpus and combined it with publicly available data. |
Alp Öktem; Eric DeLuca; Rodrigue Bashizi; Eric Paquin; Grace Tang; | arxiv-cs.CL | 2021-03-19 |
| 302 | Gumbel-Attention for Multi-modal Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel Gumbel-Attention for multi-modal machine translation, which selects the text-related parts of the image features. |
Pengbo Liu; Hailong Cao; Tiejun Zhao; | arxiv-cs.CL | 2021-03-16 |
| 303 | Towards The Evaluation of Automatic Simultaneous Speech Translation from A Communicative Perspective Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the results of an experiment aimed at evaluating the quality of a real-time speech translation engine by comparing it to the performance of professional simultaneous interpreters. |
Claudio Fantinuoli; Bianca Prandi; | arxiv-cs.CL | 2021-03-15 |
| 304 | The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present MENYO-20k, the first multi-domain parallel corpus with a special focus on clean orthography for Yor\`ub\’a–English with standardized train-test splits for benchmarking. We provide several neural MT benchmarks and compare them to the performance of popular pre-trained (massively multilingual) MT models both for the heterogeneous test set and its subdomains. |
DAVID I. ADELANI et. al. | arxiv-cs.CL | 2021-03-15 |
| 305 | Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, using Fon language as a case study, we revisit standard tokenization methods and introduce Word-Expressions-Based (WEB) tokenization, a human-involved super-words tokenization strategy to create a better representative vocabulary for training. |
Bonaventure F. P. Dossou; Chris C. Emezue; | arxiv-cs.CL | 2021-03-14 |
| 306 | Visual Cues and Error Correction for Translation Robustness Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on three types of realistic noise that are commonly generated by humans and introduce the idea of visual context to improve translation robustness for noisy texts. |
Zhenhao Li; Marek Rei; Lucia Specia; | arxiv-cs.CL | 2021-03-12 |
| 307 | Learning Feature Weights Using Reward Modeling for Denoising Parallel Corpora Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents an alternative approach which learns weights for multiple sentence-level features. |
Gaurav Kumar; Philipp Koehn; Sanjeev Khudanpur; | arxiv-cs.CL | 2021-03-11 |
| 308 | Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we look into adding a new language to a multilingual NMT system in an unsupervised fashion. |
Carlos Mullov; Ngoc-Quan Pham; Alexander Waibel; | arxiv-cs.CL | 2021-03-11 |
| 309 | Bilingual Dictionary-based Language Model Pretraining for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate the need for expensive parallel corpora by TLM, in this work, we incorporate the translation information from dictionaries into the pretraining process and propose a novel Bilingual Dictionary-based Language Model (BDLM). |
Yusen Lin; Jiayong Lin; Shuaicheng Zhang; Haoying Dai; | arxiv-cs.CL | 2021-03-11 |
| 310 | Translating The Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we perform fine-grained analysis on how an SMT system compares with two NMT systems (BiLSTM and Transformer) when translating bare nouns in Yor\`ub\’a into English. |
Ife Adebara; Muhammad Abdul-Mageed; Miikka Silfverberg; | arxiv-cs.CL | 2021-03-06 |
| 311 | Multichannel LSTM-CNN for Telugu Technical Domain Identification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed the Multichannel LSTM-CNN methodology for Technical Domain Identification for Telugu. |
Sunil Gundapu; Radhika Mamidi; | arxiv-cs.CL | 2021-02-24 |
| 312 | Machine Translation Customization Via Automatic Training Data Selection from The Web Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe an approach for customizing MT systems on specific domains by selecting data similar to the target customer data to train neural translation models. |
Thuy Vu; Alessandro Moschitti; | arxiv-cs.CL | 2021-02-19 |
| 313 | Crowdsourcing Parallel Corpus for English-Oromo Neural Machine Translation Using Community Engagement Platform Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The paper deals with implementing a translation of English to Afaan Oromo and vice versa using Neural Machine Translation. |
SISAY CHALA et. al. | arxiv-cs.AI | 2021-02-15 |
| 314 | Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study zero-shot translation using language-specific encoders-decoders. |
JUNWEI LIAO et. al. | arxiv-cs.CL | 2021-02-12 |
| 315 | Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Experiments on three translation directions show that by fine-tuning from FAT-MLM, our proposed speech translation models substantially improve translation quality by up to +5.9 BLEU. |
Renjie Zheng; Junkun Chen; Mingbo Ma; Liang Huang; | arxiv-cs.CL | 2021-02-10 |
| 316 | Self-supervised Bilingual Syntactic Alignment for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work shows the first attempt of a source-target bilingual syntactic alignment approach SyntAligner by mutual information maximization-based self-supervised neural deep modeling. |
Tianfu Zhang; Heyan Huang; Chong Feng; Longbing Cao; | aaai | 2021-02-09 |
| 317 | Learning Light-Weight Translation Models from Deep Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we take a natural step towards learning strong but light-weight NMT systems. |
BEI LI et. al. | aaai | 2021-02-09 |
| 318 | Empirical Regularization for Synthetic Sentence Pairs in Unsupervised Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we empirically study the core training procedure of UNMT to analyze the synthetic sentence pairs obtained from back-translation. |
Xi Ai; Bin Fang; | aaai | 2021-02-09 |
| 319 | Bridging The Domain Gap: Improve Informal Language Translation Via Counterfactual Domain Adaptation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose a counterfactual domain adaptation method to better leverage both large-scale source-domain data (formal texts) and small-scale target-domain data (informal texts). |
Ke Wang; Guandan Chen; Zhongqiang Huang; Xiaojun Wan; Fei Huang; | aaai | 2021-02-09 |
| 320 | Towards Fully Automated Manga Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we make the following four contributions that establishes the foundation of manga translation research. |
Ryota Hinami; Shonosuke Ishiwatari; Kazuhiko Yasuda; Yusuke Matsui; | aaai | 2021-02-09 |
| 321 | Accelerating Neural Machine Translation with Partial Word Embedding Compression Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Partial Vector Quantization (P-VQ) for NMT models, which can both compress the word embedding matrix and accelerate word probability prediction in the softmax layer. |
Fan Zhang; Mei Tu; Jinyao Yan; | aaai | 2021-02-09 |
| 322 | Listen, Understand and Translate: Triple Supervision Decouples End-to-end Speech-to-text Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Listen-Understand-Translate, (LUT), a unified framework with triple supervision signals to decouple the end-to-end speech-to-text translation task. |
QIANQIAN DONG et. al. | aaai | 2021-02-09 |
| 323 | Multilingual Transfer Learning for QA Using Translation As Data Augmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore strategies that improve cross-lingual transfer by bringing the multilingual embeddings closer in the semantic space. |
Mihaela Bornea; Lin Pan; Sara Rosenthal; Radu Florian; Avirup Sil; | aaai | 2021-02-09 |
| 324 | Understanding Pre-Editing for Black-Box Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To elicit such understanding, we extensively investigated human pre-editing practices. |
Rei Miyata; Atsushi Fujita; | arxiv-cs.CL | 2021-02-04 |
| 325 | Studying The Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we empirically investigate how the T5 model performs when pre-trained and fine-tuned to support code-related tasks. |
ANTONIO MASTROPAOLO et. al. | arxiv-cs.SE | 2021-02-03 |
| 326 | Transition Based Graph Decoder for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a general Transformer-based approach for tree and graph decoding based on generating a sequence of transitions, inspired by a similar approach that uses RNNs by Dyer (2016). |
Leshem Choshen; Omri Abend; | arxiv-cs.CL | 2021-01-29 |
| 327 | GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we demonstrate conditional computation as a remedy to the above mentioned impediments, and demonstrate its efficacy and utility. |
DMITRY LEPIKHIN et. al. | iclr | 2021-01-21 |
| 328 | Uncertainty Estimation in Autoregressive Structured Prediction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A Deep Investigation of Ensemble-based Uncertainty Estimation for Autoregressive ASR and NMT models. |
Andrey Malinin; Mark Gales; | iclr | 2021-01-21 |
| 329 | On Learning Universal Representations Across Languages IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend pre-trained language models to learn universal representations among multiple languages, and show the effectiveness on cross-lingual understanding and generation. |
XIANGPENG WEI et. al. | iclr | 2021-01-21 |
| 330 | GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work introduces GENIE, an extensible human evaluation leaderboard, which brings the ease of leaderboards to text generation tasks. We introduce several datasets in English to GENIE, representing four core challenges in text generation: machine translation, summarization, commonsense reasoning, and machine comprehension. |
DANIEL KHASHABI et. al. | arxiv-cs.CL | 2021-01-16 |
| 331 | The Impact of Post-editing and Machine Translation on Creativity and Reading Experience Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article presents the results of a study involving the translation of a fictional story from English into Catalan in three modalities: machine-translated (MT), post-edited (MTPE) and translated without aid (HT). |
Ana Guerberof Arenas; Antonio Toral; | arxiv-cs.CL | 2021-01-15 |
| 332 | Context- and Sequence-Aware Convolutional Recurrent Encoder for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Existing models use recurrent neural networks to construct both the encoder and decoder modules. |
Ritam Mallick; Seba Susan; Vaibhaw Agrawal; Rizul Garg; Prateek Rawal; | arxiv-cs.CL | 2021-01-11 |
| 333 | Improving Neural Machine Translation with Sentence Alignment Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract Neural machine translation (NMT) optimized by maximum likelihood estimation (MLE) usually lacks the guarantee of translation adequacy. To alleviate this problem, we … |
Xuewen Shi; Heyan Huang; Ping Jian; Yi-Kun Tang; | Neurocomputing | 2021-01-01 |
| 334 | ATLASLang NMT: Arabic Text Language Into Arabic Sign Language Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract ATLASLang is a machine translation system from Arabic text language into Arabic sign language (ArSL). The first version of the system (Brour and Benabbou, 2019) is based … |
Mourad Brour; Abderrahim Benabbou; | J. King Saud Univ. Comput. Inf. Sci. | 2021-01-01 |
| 335 | Prolexbase: Une Ontologie Pour Le Traitement Multilingue Des Noms Propres Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Proper names often constitute a problem in translation. This contribution deals with an ontology which represents the basis for a multilingual database of proper names, … |
Thierry Grass; Denis Maurel; Mickaël Tran; | Linguistica Antverpiensia, New Series – Themes in … | 2021-01-01 |
| 336 | Multi-modal Neural Machine Translation with Deep Semantic Interactions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract Based on the conventional attentional encoder-decoder framework, multi-modal neural machine translation (NMT) further incorporates spatial visual features through a … |
JINSONG SU et. al. | Inf. Sci. | 2021-01-01 |
| 337 | MuST-C: A Multilingual Corpus for End-to-end Speech Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract End-to-end spoken language translation (SLT) has recently gained popularity thanks to the advancement of sequence to sequence learning in its two parent tasks: automatic … |
ROLDANO CATTONI et. al. | Comput. Speech Lang. | 2021-01-01 |
| 338 | CoMeT: Towards Code-Mixed Translation Using Parallel Monolingual Sentences Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Code-mixed languages are very popular in multilingual societies around the world, yet the resources lag behind to enable robust systems on such languages. A major contributing … |
DEVANSH GAUTAM et. al. | 2021-01-01 | |
| 339 | Unsupervised Statistical Text Simplification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Most recent approaches for Text Simplification (TS) have drawn on insights from machine translation to learn simplification rewrites from the monolingual parallel corpus of … |
Jipeng Qiang; Xindong Wu; | IEEE Transactions on Knowledge and Data Engineering | 2021-01-01 |
| 340 | Interpretation and Machine Translation Towards Google Translate As A Part of Machine Translation and Teaching Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Language comprehension is the capacity of someone to properly understand the language to fully communicate the message and details. When dialects are distinct, the problem arises. … |
Vichard L. Kane; | Applied Translation | 2021-01-01 |
| 341 | Automatic Translation of Spoken English Based on Improved Machine Learning Algorithm Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Due to the complexity of English machine translation technology and its broad application prospects, many experts and scholars have invested more energy to analyze it. In view of … |
Lin Lin; Jie Liu; Xuebing Zhang; Xiufang Liang; | J. Intell. Fuzzy Syst. | 2021-01-01 |
| 342 | Findings of The AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of The Americas Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: This paper presents the results of the 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas. The shared task featured two independent tracks, and … |
MANUEL MAGER et. al. | 2021-01-01 | |
| 343 | The Usefulness of Bibles in Low-Resource Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Bibles are available in a wide range of languages, which provides valuable parallel text between languages since verses can be aligned accurately between all the different … |
Ling Liu; Zach Ryan; Mans Hulden; | Proceedings of the Workshop on Computational Methods for … | 2021-01-01 |
| 344 | Errors of Machine Translation of Terminology in The Patent Text from English Into Chinese Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: This paper summarizes eight types of error of terminology in the patent text in the output of Machine Translation from English into Chinese, including term being mistranslated as … |
Ying Cheng; Shuyu Yue; Jing Li; Lin Deng; Qi Quan; | 2021-01-01 | |
| 345 | Multimedia Interaction-Based Computer-Aided Translation Technology in Applied English Teaching Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Multimedia interaction-based computer-aided translation (CAT) is an effective method for translating massive multimedia applications. It is an essential English learning tool for … |
Hongxia Wu; | Mob. Inf. Syst. | 2021-01-01 |
| 346 | UoB at ProfNER 2021: Data Augmentation for Classification Using Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: This paper describes the participation of the UoB-NLP team in the ProfNER-ST shared subtask 7a. The task was aimed at detecting the mention of professions in social media text. … |
Frances Adriana Laureano De Leon; Harish Tayyar Madabushi; Mark Lee; | 2021-01-01 | |
| 347 | Transformer-Based Direct Speech-To-Speech Translation with Transcoder Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Traditional speech translation systems use a cascade manner that concatenates speech recognition (ASR), machine translation (MT), and text-to-speech (TTS) synthesis to translate … |
Takatomo Kano; Sakriani Sakti; Satoshi Nakamura; | 2021 IEEE Spoken Language Technology Workshop (SLT) | 2021-01-01 |
| 348 | The COVID-19 Fake News Detection in Thai Social Texts Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: One important obstruction against Thai COVID-19 recovery is fake news shared on social media that is one of the “ Artificial Intelligence Open Issues against COVID-19 ” reported … |
Pakpoom Mookdarsanit; Lawankorn Mookdarsanit; | Bulletin of Electrical Engineering and Informatics | 2021-01-01 |
| 349 | Should We Find Another Model?: Improving Neural Machine Translation Performance with ONE-Piece Tokenization Method Without Model Modification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Most of the recent Natural Language Processing(NLP) studies are based on the Pretrain-Finetuning Approach (PFA), but in small and medium-sized enterprises or companies with … |
Chanjun Park; Sugyeong Eo; Hyeonseok Moon; Heuiseok Lim; | 2021-01-01 | |
| 350 | FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To motivate wider investigation in such a scenario, we present a real-world fine-grained domain adaptation task in machine translation (FGraDA). |
WENHAO ZHU et. al. | arxiv-cs.CL | 2020-12-31 |
| 351 | Vocabulary Learning Via Optimal Transport for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose VOLT, a simple and efficient solution without trial training. |
Jingjing Xu; Hao Zhou; Chun Gan; Zaixiang Zheng; Lei Li; | arxiv-cs.CL | 2020-12-31 |
| 352 | Revisiting Robust Neural Machine Translation: A Transformer Case Study Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we try to investigate how noise breaks Transformers and if there exist solutions to deal with such issues. |
Peyman Passban; Puneeth S. M. Saladi; Qun Liu; | arxiv-cs.CL | 2020-12-31 |
| 353 | Fully Synthetic Data Improves Neural Machine Translation with Knowledge Distillation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper explores augmenting monolingual data for knowledge distillation in neural machine translation. |
Alham Fikri Aji; Kenneth Heafield; | arxiv-cs.CL | 2020-12-31 |
| 354 | Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, our main contribution is to take a step further in understanding EncoderFusion. |
XUEBO LIU et. al. | arxiv-cs.CL | 2020-12-29 |
| 355 | Understanding and Improving Lexical Choice in Non-Autoregressive Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we empirically show that as a side effect of this training, the lexical choice errors on low-frequency words are propagated to the NAT model from the teacher model. |
LIANG DING et. al. | arxiv-cs.CL | 2020-12-28 |
| 356 | Neural Text Generation With Artificial Negative Examples Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to suppress an arbitrary type of errors by training the text generation model in a reinforcement learning framework, where we use a trainable reward function that is capable of discriminating between references and sentences containing the targeted type of errors. |
Keisuke Shirai; Kazuma Hashimoto; Akiko Eriguchi; Takashi Ninomiya; Shinsuke Mori; | arxiv-cs.CL | 2020-12-28 |
| 357 | Domain Adaptation Of NMT Models For English-Hindi Machine Translation Task At AdapMT ICON 2020 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the neural machine translation systems for the English-Hindi language presented in AdapMT Shared Task ICON 2020. |
Ramchandra Joshi; Rushabh Karnavat; Kaustubh Jirapure; Raviraj Joshi; | arxiv-cs.CL | 2020-12-22 |
| 358 | Subword Sampling for Low Resource Word Alignment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose subword sampling-based alignment of text units. |
Ehsaneddin Asgari; Masoud Jalili Sabet; Philipp Dufter; Christopher Ringlstetter; Hinrich Schütze; | arxiv-cs.CL | 2020-12-21 |
| 359 | Improving Multilingual Neural Machine Translation For Low-Resource Languages: French,English – Vietnamese Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes two simple strategies to address the rare word issue in multilingual MT systems for two low-resource language pairs: French-Vietnamese and English-Vietnamese. |
Thi-Vinh Ngo; Phuong-Thai Nguyen; Thanh-Le Ha; Khac-Quy Dinh; Le-Minh Nguyen; | arxiv-cs.CL | 2020-12-15 |
| 360 | Modeling Homophone Noise For Robust Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a robust neural machine translation (NMT) framework. |
WENJIE QIN et. al. | arxiv-cs.CL | 2020-12-15 |
| 361 | MSVD-Turkish: A Comprehensive Multimodal Dataset For Integrated Vision And Language Research In Turkish Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we target Turkish, a morphologically rich and agglutinative language that has very different properties compared to English. |
BEGUM CITAMAK et. al. | arxiv-cs.CV | 2020-12-13 |
| 362 | Document-aligned Japanese-English Conversation Parallel Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the first issue, we present a document-aligned Japanese-English conversation corpus, including balanced, high-quality business conversation data for tuning and testing. |
Matīss Rikters; Ryokan Ri; Tong Li; Toshiaki Nakazawa; | arxiv-cs.CL | 2020-12-11 |
| 363 | Automatic Standardization Of Colloquial Persian Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes a simple and effective standardization approach based on sequence-to-sequence translation. Moreover, we annotate a publicly available evaluation data consisting of 1912 sentences from a diverse set of domains. |
Mohammad Sadegh Rasooli; Farzane Bakhtyari; Fatemeh Shafiei; Mahsa Ravanbakhsh; Chris Callison-Burch; | arxiv-cs.CL | 2020-12-10 |
| 364 | Breeding Gender-aware Direct Speech Translation Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Going beyond speech signals, in this paper we compare different approaches to inform direct ST models about the speaker’s gender and test their ability to handle gender translation from English into Italian and French. |
Marco Gaido; Beatrice Savoldi; Luisa Bentivogli; Matteo Negri; Marco Turchi; | arxiv-cs.CL | 2020-12-09 |
| 365 | Rewriter-Evaluator Architecture for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we present a novel architecture, Rewriter-Evaluator. |
Yangming Li; Kaisheng Yao; | arxiv-cs.CL | 2020-12-09 |
| 366 | Towards Annotation-Free Evaluation Of Cross-Lingual Image Captioning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to save the precious human resource from re-writing reference sentences per target language, in this paper we make a brave attempt towards annotation-free evaluation of cross-lingual image captioning. |
Aozhu Chen; Xinyi Huang; Hailan Lin; Xirong Li; | arxiv-cs.CV | 2020-12-09 |
| 367 | On Knowledge Distillation For Direct Speech Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we compare the different solutions to distill knowledge in a sequence-to-sequence task like ST. Moreover, we analyze eventual drawbacks of this approach and how to alleviate them maintaining the benefits in terms of translation quality. |
Marco Gaido; Mattia A. Di Gangi; Matteo Negri; Marco Turchi; | arxiv-cs.CL | 2020-12-09 |
| 368 | Document Graph for Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Previous works have shown that contextual information can improve the performance of neural machine translation (NMT). |
Mingzhou Xu; Liangyou Li; Derek. F. Wong; Qun Liu; Lidia S. Chao; | arxiv-cs.CL | 2020-12-07 |
| 369 | A Benchmark Dataset For Understandable Medical Language Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce MedLane — a new human-annotated Medical Language translation dataset, to align professional medical sentences with layperson-understandable expressions. |
JUNYU LUO et. al. | arxiv-cs.CL | 2020-12-04 |
| 370 | A Simple And Effective Approach To Robust Unsupervised Bilingual Dictionary Induction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that this failure results from the gap between the actual initialization performance and the minimum initialization performance for the self-learning to succeed. |
YANYANG LI et. al. | arxiv-cs.CL | 2020-11-30 |
| 371 | Machine Translation Of Novels In The Age Of Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this chapter we build a machine translation (MT) system tailored to the literary domain, specifically to novels, based on the state-of-the-art architecture in neural MT (NMT), the Transformer (Vaswani et al., 2017), for the translation direction English-to-Catalan. |
Antonio Toral; Antoni Oliver; Pau Ribas Ballestín; | arxiv-cs.CL | 2020-11-30 |
| 372 | Using Multiple Subwords To Improve English-Esperanto Automated Literary Translation Quality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To that end, in this paper we propose employing the same parallel sentences multiple times, only changing the way the words are split each time. |
Alberto Poncelas; Jan Buts; James Hadley; Andy Way; | arxiv-cs.CL | 2020-11-28 |
| 373 | A Panoramic Survey of Natural Language Processing in The Arab World Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: NLP researchers pride themselves on developing language independent models and tools that can be applied to all human languages, e.g. machine translation systems can be built for a variety of languages using the same basic mechanisms and models. |
KAREEM DARWISH et. al. | arxiv-cs.CL | 2020-11-25 |
| 374 | Two-Way Neural Machine Translation: A Proof Of Concept For Bidirectional Translation Modeling Using A Two-Dimensional Grid Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes to build a single end-to-end bidirectional translation model using a two-dimensional grid, where the left-to-right decoding generates source-to-target, and the bottom-to-up decoding creates target-to-source output. |
Parnia Bahar; Christopher Brix; Hermann Ney; | arxiv-cs.CL | 2020-11-24 |
| 375 | The Ubiqus English-Inuktitut System For WMT20 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Ubiqus’ submission to the WMT20 English-Inuktitut shared news translation task. |
François Hernandez; Vincent Nguyen; | arxiv-cs.CL | 2020-11-18 |
| 376 | Data Diversification: A Simple Strategy For Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Data Diversification: a simple but effective strategy to boost neural machine translation (NMT) performance. |
Xuan-Phi Nguyen; Shafiq Joty; Kui Wu; Ai Ti Aw; | nips | 2020-11-17 |
| 377 | Deep Transformers With Latent Depth IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a probabilistic framework to automatically learn which layer(s) to use by learning the posterior distributions of layer selection. |
Xian Li; Asa Cooper Stickland; Yuqing Tang; Xiang Kong; | nips | 2020-11-17 |
| 378 | Cross-lingual Retrieval For Iterative Self-Supervised Training IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we found that the cross-lingual alignment can be further improved by training seq2seq models on sentence pairs mined using their own encoder outputs. |
Chau Tran; Yuqing Tang; Xian Li; Jiatao Gu; | nips | 2020-11-17 |
| 379 | Is Normalization Indispensable For Training Deep Neural Network? IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study what would happen when normalization layers are removed from the network, and show how to train deep neural networks without normalization layers and without performance degradation. |
Jie Shao; Kai Hu; Changhu Wang; Xiangyang Xue; Bhiksha Raj; | nips | 2020-11-17 |
| 380 | All Word Embeddings From One Embedding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, to reduce the total number of parameters, the embeddings for all words are represented by transforming a shared embedding. |
Sho Takase; Sosuke Kobayashi; | nips | 2020-11-17 |
| 381 | Incorporating BERT Into Parallel Sequence Decoding With Adapters IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to address this problem by taking two different BERT models as the encoder and decoder respectively, and fine-tuning them by introducing simple and lightweight adapter modules, which are inserted between BERT layers and tuned on the task-specific dataset. |
JUNLIANG GUO et. al. | nips | 2020-11-17 |
| 382 | Facebook AI’s WMT20 News Translation Task Submission IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Facebook AI’s submission to WMT20 shared news translation task. |
PENG-JEN CHEN et. al. | arxiv-cs.CL | 2020-11-16 |
| 383 | A Hybrid Approach for Improved Low Resource Neural Machine Translation Using Monolingual Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work, therefore, proposes a novel approach that enables both the backward and forward models to benefit from the monolingual target data through a hybrid of self-learning and back-translation respectively. |
Idris Abdulmumin; Bashir Shehu Galadanci; Abubakar Isa; Habeebah Adamu Kakudi; Ismaila Idris Sinan; | arxiv-cs.CL | 2020-11-14 |
| 384 | EDITOR: An Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce an Edit-Based Transformer with Repositioning (EDITOR), which makes sequence generation flexible by seamlessly allowing users to specify preferences in output lexical choice. |
Weijia Xu; Marine Carpuat; | arxiv-cs.CL | 2020-11-13 |
| 385 | Language Models Not Just For Pre-training: Fast Online Neural Noisy Channel Modeling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We address this issue by introducing efficient approximations to make inference with the noisy channel approach as fast as strong ensembles while increasing accuracy. |
Shruti Bhosale; Kyra Yee; Sergey Edunov; Michael Auli; | arxiv-cs.CL | 2020-11-13 |
| 386 | Losing Heads In The Lottery: Pruning Transformer Attention In Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we apply the lottery ticket hypothesis to prune heads in the early stages of training. |
Maximiliana Behnke; Kenneth Heafield; | emnlp | 2020-11-12 |
| 387 | Statistical Power And Translationese In Machine Translation Evaluation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The term translationese has been used to describe features of translated text, and in this paper, we provide detailed analysis of potential adverse effects of translationese on machine translation evaluation. |
Yvette Graham; Barry Haddow; Philipp Koehn; | emnlp | 2020-11-12 |
| 388 | Improving AMR Parsing With Sequence-to-Sequence Pre-training IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on sequence-to-sequence (seq2seq) AMR parsing and propose a seq2seq pre-training approach to build pre-trained models in both single and joint way on three relevant tasks, i.e., machine translation, syntactic parsing, and AMR parsing itself. |
Dongqin Xu; Junhui Li; Muhua Zhu; Min Zhang; Guodong Zhou; | emnlp | 2020-11-12 |
| 389 | X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a method to automatically construct an SRL corpus that is parallel in four languages: English, French, German, Spanish, with unified predicate and role annotations that are fully comparable across languages. |
Angel Daza; Anette Frank; | emnlp | 2020-11-12 |
| 390 | Why Skip If You Can Combine: A Simple Knowledge Distillation Technique For Intermediate Layers IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we target low-resource settings and evaluate our translation engines for Portuguese?English, Turkish?English, and English?German directions. |
Yimeng Wu; Peyman Passban; Mehdi Rezagholizadeh; Qun Liu; | emnlp | 2020-11-12 |
| 391 | Inference-only Sub-character Decomposition Improves Translation Of Unseen Logographic Characters Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate existing ideograph-based sub-character decomposition approaches for Chinese-to-English and Japanese-to-English NMT, for both high-resource and low-resource domains. |
Danielle Saunders; Weston Feely; Bill Byrne; | arxiv-cs.CL | 2020-11-12 |
| 392 | Detecting Fine-Grained Cross-Lingual Semantic Divergences Without Supervision By Learning To Rank Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a training strategy for multilingual BERT models by learning to rank synthetic divergent examples of varying granularity. |
Eleftheria Briakou; Marine Carpuat; | emnlp | 2020-11-12 |
| 393 | Simultaneous Machine Translation With Visual Context Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we seek to understand whether the addition of visual information can compensate for the missing source context. |
OZAN CAGLAYAN et. al. | emnlp | 2020-11-12 |
| 394 | Simulated Multiple Reference Training Improves Low-resource Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Simulated Multiple Reference Training (SMRT), a novel MT training method that approximates the full space of possible translations by sampling a paraphrase of the reference sentence from a paraphraser and training the MT model to predict the paraphraser’s distribution over possible tokens. |
Huda Khayrallah; Brian Thompson; Matt Post; Philipp Koehn; | emnlp | 2020-11-12 |
| 395 | Multi-Unit Transformers For Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose the Multi-Unit Transformer (MUTE) , which aim to promote the expressiveness of the Transformer by introducing diverse and complementary units. |
Jianhao Yan; Fandong Meng; Jie Zhou; | emnlp | 2020-11-12 |
| 396 | BLEU Might Be Guilty But References Are Not Innocent IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study different methods to collect references and compare their value in automated evaluation by reporting correlation with human evaluation for a variety of systems and metrics. |
Markus Freitag; David Grangier; Isaac Caswell; | emnlp | 2020-11-12 |
| 397 | Reusing A Pretrained Language Model On Languages With Limited Corpora For Unsupervised NMT IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an effective approach that reuses an LM that is pretrained only on the high-resource language. |
Alexandra Chronopoulou; Dario Stojanovski; Alexander Fraser; | emnlp | 2020-11-12 |
| 398 | Localizing Open-Ontology QA Semantic Parsers In A Day Using Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Semantic Parser Localizer (SPL), a toolkit that leverages Neural Machine Translation (NMT) systems to localize a semantic parser for a new language. |
Mehrad Moradshahi; Giovanni Campagna; Sina Semnani; Silei Xu; Monica Lam; | emnlp | 2020-11-12 |
| 399 | Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, And New Datasets For Bengali-English Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we build a customized sentence segmenter for Bengali and propose two novel methods for parallel corpus creation on low-resource setups: aligner ensembling and batch filtering. We release the segmenter, parallel corpus, and the evaluation set, thus elevating Bengali from its low-resource status. |
TAHMID HASAN et. al. | emnlp | 2020-11-12 |
| 400 | ChrEn: Cherokee-English Machine Translation For Endangered Language Revitalization IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To help save this endangered language, we introduce ChrEn, a Cherokee-English parallel dataset, to facilitate machine translation research between Cherokee and English. |
Shiyue Zhang; Benjamin Frey; Mohit Bansal; | emnlp | 2020-11-12 |
| 401 | Effectively Pretraining A Speech Translation Decoder With Machine Translation Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we will show that by using an adversarial regularizer, we can bring the encoder representations of the ASR and NMT tasks closer even though they are in different modalities, and how this helps us effectively use a pretrained NMT decoder for speech translation. |
Ashkan Alinejad; Anoop Sarkar; | emnlp | 2020-11-12 |
| 402 | Detecting Word Sense Disambiguation Biases In Machine Translation For Model-Agnostic Adversarial Attacks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a method for the prediction of disambiguation errors based on statistical data properties, demonstrating its effectiveness across several domains and model types. |
Denis Emelin; Ivan Titov; Rico Sennrich; | emnlp | 2020-11-12 |
| 403 | Pre-tokenization Of Multi-word Expressions In Cross-lingual Word Embeddings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a simple method for word translation of MWEs to and from English in ten languages: we first compile lists of MWEs in each language and then tokenize the MWEs as single tokens before training word embeddings. |
NAOKI OTANI et. al. | emnlp | 2020-11-12 |
| 404 | PyMT5: Multi-mode Translation Of Natural Language And Python Code With Transformers IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an analysis and modeling effort of a large-scale parallel corpus of 26 million Python methods and 7.7 million method-docstring pairs, demonstrating that for docstring and method generation, PyMT5 outperforms similarly-sized auto-regressive language models (GPT2) which were English pre-trained or randomly initialized. |
Colin Clement; Dawn Drain; Jonathan Timcheck; Alexey Svyatkovskiy; Neel Sundaresan; | emnlp | 2020-11-12 |
| 405 | Shallow-to-Deep Training For Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the behavior of a well-tuned deep Transformer system. |
BEI LI et. al. | emnlp | 2020-11-12 |
| 406 | Improving Word Sense Disambiguation With Translations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel approach that improves the performance of a base WSD system using machine translation. |
Yixing Luan; Bradley Hauer; Lili Mou; Grzegorz Kondrak; | emnlp | 2020-11-12 |
| 407 | An Empirical Study Of Generation Order For Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present an empirical study of generation order for machine translation. |
William Chan; Mitchell Stern; Jamie Kiros; Jakob Uszkoreit; | emnlp | 2020-11-12 |
| 408 | Data And Representation For Turkish Natural Language Inference Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we offer a positive response for natural language inference (NLI) in Turkish. |
Emrah Budur; Rıza Özçelik; Tunga Gungor; Christopher Potts; | emnlp | 2020-11-12 |
| 409 | Generating Diverse Translation From Model Distribution With Dropout Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to generate diverse translations by deriving a large number of possible models with Bayesian modelling and sampling models from them for inference. |
Xuanfu Wu; Yang Feng; Chenze Shao; | emnlp | 2020-11-12 |
| 410 | Data Rejuvenation: Exploiting Inactive Training Examples For Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore to identify the inactive training examples which contribute less to the model performance, and show that the existence of inactive examples depends on the data distribution. |
WENXIANG JIAO et. al. | emnlp | 2020-11-12 |
| 411 | Can Automatic Post-Editing Improve NMT? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We hypothesize that APE models have been underperforming in improving NMT translations due to the lack of adequate supervision. To ascertain our hypothesis, we compile a larger corpus of human post-edits of English to German NMT. |
Shamil Chollampatt; Raymond Hendy Susanto; Liling Tan; Ewa Szymanska; | emnlp | 2020-11-12 |
| 412 | TeaForN: Teacher-Forcing With N-grams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our proposed method, Teacher-Forcing with N-grams (TeaForN), addresses both these problems directly, through the use of a stack of N decoders trained to decode along a secondary time axis that allows model-parameter updates based on N prediction steps. |
Sebastian Goodman; Nan Ding; Radu Soricut; | emnlp | 2020-11-12 |
| 413 | Multi-Agent Mutual Learning At Sentence-Level And Token-Level For Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we extend mutual learning to the machine translation task and operate at both the sentence-level and the token-level. |
Baohao Liao; Yingbo Gao; Hermann Ney; | emnlp | 2020-11-10 |
| 414 | Improving Grammatical Error Correction With Machine Translation Pairs IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel data synthesis method to generate diverse error-corrected sentence pairs for improving grammatical error correction, which is based on a pair of machine translation models (e.g., Chinese to English) of different qualities (i.e., poor and good). |
WANGCHUNSHU ZHOU et. al. | emnlp | 2020-11-10 |
| 415 | Using Visual Feature Space As A Pivot Across Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our work aims to leverage visual feature space to pass information across languages. |
Ziyan Yang; Leticia Pinto-Alva; Franck Dernoncourt; Vicente Ordonez; | emnlp | 2020-11-10 |
| 416 | KoBE: Knowledge-Based Machine Translation Evaluation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a simple and effective method for machine translation evaluation which does not require reference translations. |
Zorik Gekhman; Roee Aharoni; Genady Beryozkin; Markus Freitag; Wolfgang Macherey; | emnlp | 2020-11-10 |
| 417 | Improving Target-side Lexical Transfer In Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to improve the effectiveness of multilingual transfer for NMT models that translate into the LRL, by designing a better decoder word embedding. |
Luyu Gao; Xinyi Wang; Graham Neubig; | emnlp | 2020-11-10 |
| 418 | From Unsupervised Machine Translation To Adversarial Text Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a self-attention based bilingual adversarial text generator (B-GAN) which can learn to generate text from the encoder representation of an unsupervised neural machine translation system. |
Ahmad Rashid; Alan Do-Omri; Md. Akmal Haidar; Qun Liu; Mehdi Rezagholizadeh; | arxiv-cs.CL | 2020-11-10 |
| 419 | Dual Reconstruction: A Unifying Objective For Semi-Supervised Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel dual reconstruction objective that provides a unified view of Iterative Back-Translation and Dual Learning. |
Weijia Xu; Xing Niu; Marine Carpuat; | emnlp | 2020-11-10 |
| 420 | On The Potential Of Lexico-logical Alignments For Semantic Parsing To SQL Queries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and test two methods: (1) supervised attention; (2) adopting an auxiliary objective of disambiguating references in the input queries to table columns. |
Tianze Shi; Chen Zhao; Jordan Boyd-Graber; Hal Daumé III; Lillian Lee; | emnlp | 2020-11-10 |
| 421 | Recursive Top-Down Production For Sentence Generation With Latent Trees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we present a dynamic programming algorithm that marginalises over latent binary tree structures with N leaves, allowing us to compute the likelihood of a sequence of N tokens under a latent tree model, which we maximise to train a recursive neural function. |
Shawn Tan; Yikang Shen; Alessandro Sordoni; Aaron Courville; Timothy J. O’Donnell; | emnlp | 2020-11-10 |
| 422 | Multilingual Argument Mining: Datasets And Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore the potential of transfer learning using the multilingual BERT model to address argument mining tasks in non-English languages, based on English datasets and the use of machine translation. |
Orith Toledo-Ronen; Matan Orbach; Yonatan Bilu; Artem Spector; Noam Slonim; | emnlp | 2020-11-10 |
| 423 | A Semi-supervised Approach To Generate The Code-Mixed Text Using Pre-trained Encoder And Transfer Learning IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To circumvent the data scarcity issue, we propose an effective deep learning approach for automatically generating the code-mixed text from English to multiple languages without any parallel data. |
Deepak Gupta; Asif Ekbal; Pushpak Bhattacharyya; | emnlp | 2020-11-10 |
| 424 | Neural Machine Translation For Extremely Low-Resource African Languages: A Case Study On Bambara Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first parallel data set for machine translation of Bambara into and from English and French and the first benchmark results on machine translation to and from Bambara. |
ALLAHSERA AUGUSTE TAPO et. al. | arxiv-cs.CL | 2020-11-10 |
| 425 | A Multilingual View Of Unsupervised Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a probabilistic framework for multilingual neural machine translation that encompasses supervised and unsupervised setups, focusing on unsupervised translation. |
Xavier Garcia; Pierre Foret; Thibault Sellam; Ankur Parikh; | emnlp | 2020-11-10 |
| 426 | On Long-Tailed Phenomena In Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we quantitatively characterize such long-tailed phenomena at two levels of abstraction, namely, token classification and sequence generation. |
Vikas Raunak; Siddharth Dalmia; Vivek Gupta; Florian Metze; | emnlp | 2020-11-10 |
| 427 | Bootstrapping A Crosslingual Semantic Parser Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a Transformer-based parser combining paraphrases by ensembling attention over multiple encoders and present new versions of ATIS and Overnight in German and Chinese for evaluation. |
Tom Sherborne; Yumo Xu; Mirella Lapata; | emnlp | 2020-11-10 |
| 428 | Factorized Transformer For Multi-Domain Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate these problems, we propose the Factorized Transformer, which consists of an in-depth factorization of the parameters of an NMT model, namely Transformer in this paper, into two categories: domain-shared ones that encode common cross-domain knowledge and domain-specific ones that are private for each constituent domain. |
Yongchao Deng; Hongfei Yu; Heng Yu; Xiangyu Duan; Weihua Luo; | emnlp | 2020-11-10 |
| 429 | Computer Assisted Translation With Neural Quality Estimation And Auotmatic Post-Editing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an end-to-end deep learning framework of the quality estimation and automatic post-editing of the machine translation output. |
KE WANG et. al. | emnlp | 2020-11-10 |
| 430 | Assessing Human-Parity In Machine Translation On The Segment Level Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To provide insight into these issues we carefully inspect the outputs of top-performing systems in the most recent WMT-19 news translation shared task for all language pairs in which a system either tied or outperformed human translation. |
Yvette Graham; Christian Federmann; Maria Eskevich; Barry Haddow; | emnlp | 2020-11-10 |
| 431 | SimAlign: High Quality Word Alignments Without Parallel Training Data Using Static And Contextualized Embeddings IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose word alignment methods that require no parallel data. |
Masoud Jalili Sabet; Philipp Dufter; François Yvon; Hinrich Schütze; | emnlp | 2020-11-10 |
| 432 | Simultaneous Speech-to-Speech Translation System With Neural Incremental ASR, MT, And TTS Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a newly developed, simultaneous neural speech-to-speech translation system and its evaluation. |
KATSUHITO SUDOH et. al. | arxiv-cs.CL | 2020-11-09 |
| 433 | AlphaMWE: Construction Of Multilingual Parallel Corpora With MWE Annotations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present the construction of multilingual parallel corpora with annotation of multiword expressions (MWEs). |
Lifeng Han; Gareth Jones; Alan Smeaton; | arxiv-cs.CL | 2020-11-07 |
| 434 | Template Controllable Keywords-to-text Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel neural model for the understudied task of generating text from keywords. |
Abhijit Mishra; Md Faisal Mahbub Chowdhury; Sagar Manohar; Dan Gutfreund; Karthik Sankaranarayanan; | arxiv-cs.AI | 2020-11-07 |
| 435 | Understanding Pure Character-Based Neural Machine Translation: The Case Of Translating Finnish Into English Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we conduct an investigation into pure character-based models in the case of translating Finnish into English, including exploring the ability to learn word senses and morphological inflections and the attention mechanism. |
Gongbo Tang; Rico Sennrich; Joakim Nivre; | arxiv-cs.CL | 2020-11-06 |
| 436 | An Unsupervised Method For OCR Post-Correction And Spelling Normalisation For Finnish Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We build on previous work on fully automatic unsupervised extraction of parallel data to train a character-based sequence-to-sequence NMT (neural machine translation) model to conduct OCR error correction designed for English, and adapt it to Finnish by proposing solutions that take the rich morphology of the language into account. |
Quan Duong; Mika Hämäläinen; Simon Hengchen; | arxiv-cs.CL | 2020-11-06 |
| 437 | Semi-Supervised Low-Resource Style Transfer Of Indonesian Informal To Formal Language With Iterative Forward-Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we address a style-transfer from informal to formal Indonesian as a low-resource machine translation problem. We build a new dataset of parallel sentences of informal Indonesian and its formal counterpart. |
HARYO AKBARIANTO WIBOWO et. al. | arxiv-cs.CL | 2020-11-06 |
| 438 | Data Augmentation and Terminology Integration for Domain-Specific Sinhala-English-Tamil Statistical Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper focuses on data augmentation techniques where bilingual lexicon terms are expanded based on case-markers with the objective of generating new words, to be used in Statistical machine Translation (SMT). |
Aloka Fernando; Surangika Ranathunga; Gihan Dias; | arxiv-cs.CL | 2020-11-05 |
| 439 | Subword Segmentation And A Single Bridge Language Affect Zero-Shot Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate zero-shot performance of a multilingual EN$\leftrightarrow${FR,CS,DE,FI} system trained on WMT data. |
Annette Rios; Mathias Müller; Rico Sennrich; | arxiv-cs.CL | 2020-11-03 |
| 440 | PheMT: A Phenomenon-wise Dataset For Machine Translation Robustness On User-Generated Contents Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To answer the question, we present a new dataset, PheMT, for evaluating the robustness of MT systems against specific linguistic phenomena in Japanese-English translation. |
RYO FUJII et. al. | arxiv-cs.CL | 2020-11-03 |
| 441 | Tilde At WMT 2020: News Task Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Tilde’s submission to the WMT2020 shared task on news translation for both directions of the English-Polish language pair in both the constrained and the unconstrained tracks. |
Rihards Krišlauks; Mārcis Pinnis; | arxiv-cs.CL | 2020-10-29 |
| 442 | The Volctrans Machine Translation System For WMT20 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our VolcTrans system on WMT20 shared news translation task. |
LIWEI WU et. al. | arxiv-cs.CL | 2020-10-28 |
| 443 | Bridging The Modality Gap For Speech-to-Text Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these issues, we propose a Speech-to-Text Adaptation for Speech Translation (STAST) model which aims to improve the end-to-end model performance by bridging the modality gap between speech and text. |
Yuchen Liu; Junnan Zhu; Jiajun Zhang; Chengqing Zong; | arxiv-cs.CL | 2020-10-28 |
| 444 | Is It Great Or Terrible? Preserving Sentiment In Neural Machine Translation Of Arabic Reviews Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we investigate the challenges involved in translating book reviews from Arabic into English, with particular focus on the errors that lead to incorrect translation of sentiment polarity. |
Hadeel Saadany; Constantin Orasan; | arxiv-cs.CL | 2020-10-26 |
| 445 | Data Troubles In Sentence Level Confidence Estimation For Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a side product of the data annotation process necessary for building such models we propose sentence level accuracy $SACC$ as a simple, self-explanatory evaluation metric for quality of translation. |
CIPRIAN CHELBA et. al. | arxiv-cs.CL | 2020-10-26 |
| 446 | The LMU Munich System For The WMT 2020 Unsupervised Machine Translation Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the submission of LMU Munich to the WMT 2020 unsupervised shared task, in two language directions, German<->Upper Sorbian. |
Alexandra Chronopoulou; Dario Stojanovski; Viktor Hangya; Alexander Fraser; | arxiv-cs.CL | 2020-10-25 |
| 447 | Context-aware Decoder for Neural Machine Translation Using A Target-side Document-Level Language Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We therefore present a simple method to turn a sentence-level translation model into a context-aware model by incorporating a document-level language model into the decoder. |
Amane Sugiyama; Naoki Yoshinaga; | arxiv-cs.CL | 2020-10-24 |
| 448 | Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we hypothesize and empirically verify that AT and NAT encoders capture different linguistic properties of source sentences. |
YONGCHANG HAO et. al. | arxiv-cs.CL | 2020-10-24 |
| 449 | CUNI Systems For The Unsupervised And Very Low Resource Translation Task In WMT20 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a description of CUNI systems submitted to the WMT20 task on unsupervised and very low-resource supervised machine translation between German and Upper Sorbian. |
Ivana Kvapilíková; Tom Kocmi; Ondřej Bojar; | arxiv-cs.CL | 2020-10-22 |
| 450 | XOR QA: Cross-lingual Open-Retrieval Question Answering IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this dataset, we introduce three new tasks that involve cross-lingual document retrieval using multi-lingual and English resources. We construct a large-scale dataset built on questions from TyDi QA lacking same-language answers. |
AKARI ASAI et. al. | arxiv-cs.CL | 2020-10-22 |
| 451 | On The Potential Of Lexico-logical Alignments For Semantic Parsing To SQL Queries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and test two methods: (1) supervised attention; (2) adopting an auxiliary objective of disambiguating references in the input queries to table columns. |
Tianze Shi; Chen Zhao; Jordan Boyd-Graber; Hal Daumé III; Lillian Lee; | arxiv-cs.CL | 2020-10-21 |
| 452 | A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a general multi-task learning framework to leverage text data for ASR and ST tasks. |
Yun Tang; Juan Pino; Changhan Wang; Xutai Ma; Dmitriy Genzel; | arxiv-cs.CL | 2020-10-21 |
| 453 | TMT: A Transformer-based Modal Translator For Improving Multimodal Sequence Representations In Audio Visual Scene-aware Dialog Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by Neural Machine Translation (NMT), we propose the Transformer-based Modal Translator (TMT) to learn the representations of the source modal sequence by translating the source modal sequence to the related target modal sequence in a supervised manner. |
Wubo Li; Dongwei Jiang; Wei Zou; Xiangang Li; | arxiv-cs.CL | 2020-10-21 |
| 454 | Beyond English-Centric Multilingual Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we create a true Many-to-Many multilingual translation model that can translate directly between any pair of 100 languages. We build and open source a training dataset that covers thousands of language directions with supervised data, created through large-scale mining. |
ANGELA FAN et. al. | arxiv-cs.CL | 2020-10-21 |
| 455 | Cascaded Models With Cyclic Feedback For Direct Speech Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a technique that allows cascades of automatic speech recognition (ASR) and machine translation (MT) to exploit in-domain direct speech translation data in addition to out-of-domain MT and ASR data. |
Tsz Kin Lam; Shigehiko Schamoni; Stefan Riezler; | arxiv-cs.CL | 2020-10-21 |
| 456 | Token Drop Mechanism For Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Token Drop to improve generalization and avoid overfitting for the NMT model. |
Huaao Zhang; Shigui Qiu; Xiangyu Duan; Min Zhang; | arxiv-cs.CL | 2020-10-21 |
| 457 | Towards End-to-End In-Image Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing the same text in another language. |
ELMAN MANSIMOV et. al. | arxiv-cs.CL | 2020-10-20 |
| 458 | Human-Paraphrased References Improve Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we compare the results of performing end-to-end system development using standard and paraphrased references. |
Markus Freitag; George Foster; David Grangier; Colin Cherry; | arxiv-cs.CL | 2020-10-20 |
| 459 | Complete Multilingual Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Multilingual Neural Machine Translation (MNMT) models are commonly trained on a joint set of bilingual corpora which is acutely English-centric (i.e. English either as the source or target language). |
Markus Freitag; Orhan Firat; | arxiv-cs.CL | 2020-10-20 |
| 460 | Incorporating Terminology Constraints In Automatic Post-Editing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Users of machine translation (MT) may want to ensure the use of specific lexical terminologies. While there exist techniques for incorporating terminology constraints during … |
David Wan; Chris Kedzie; Faisal Ladhak; Marine Carpuat; Kathleen McKeown; | arxiv-cs.CL | 2020-10-19 |
| 461 | A Corpus For English-Japanese Multimodal Neural Machine Translation With Comparable Sentences Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new multimodal English-Japanese corpus with comparable sentences that are compiled from existing image captioning datasets. |
Andrew Merritt; Chenhui Chu; Yuki Arase; | arxiv-cs.CL | 2020-10-17 |
| 462 | Incorporate Semantic Structures Into Machine Translation Evaluation Via UCCA Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this work, we define words carrying important semantic meanings in sentences as semantic core words. |
Jin Xu; Yinuo Guo; Junfeng Hu; | arxiv-cs.CL | 2020-10-17 |
| 463 | DiDi’s Machine Translation System For WMT2020 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes DiDi AI Labs’ submission to the WMT2020 news translation shared task. |
TANFANG CHEN et. al. | arxiv-cs.CL | 2020-10-16 |
| 464 | Unsupervised Bitext Mining And Translation Via Self-trained Contextual Embeddings IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe an unsupervised method to create pseudo-parallel corpora for machine translation (MT) from unaligned text. |
Phillip Keung; Julian Salazar; Yichao Lu; Noah A. Smith; | arxiv-cs.CL | 2020-10-15 |
| 465 | Multi-Task Learning For Cross-Lingual Abstractive Summarization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a multi-task learning framework for cross-lingual abstractive summarization to augment training data. Recent studies constructed pseudo cross-lingual abstractive summarization data to train their neural encoder-decoders. Meanwhile, we introduce existing genuine data such as translation pairs and monolingual abstractive summarization data into training. |
Sho Takase; Naoaki Okazaki; | arxiv-cs.CL | 2020-10-15 |
| 466 | Mitigating Gender Bias In Machine Translation With Target Gender Annotations IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this work, we propose to decouple the task of acquiring the necessary information from the task of learning to translate correctly when such information is available. |
Artūrs Stafanovičs; Toms Bergmanis; Mārcis Pinnis; | arxiv-cs.CL | 2020-10-13 |
| 467 | Fine-grained Linguistic Evaluation For State-of-the-art Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes a test suite submission providing detailed statistics of linguistic performance for the state-of-the-art German-English systems of the Fifth Conference of Machine Translation (WMT20). |
Eleftherios Avramidis; Vivien Macketanz; Ursula Strohriegel; Aljoscha Burchardt; Sebastian Möller; | arxiv-cs.CL | 2020-10-13 |
| 468 | Dynamic Context-guided Capsule Network For Multimodal Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the above issues, in this paper, we propose a novel Dynamic Context-guided Capsule Network (DCCN) for MMT. |
HUAN LIN et. al. | mm | 2020-10-12 |
| 469 | Exemplar-Controllable Paraphrasing and Translation Using Bitext Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Despite only using bitext for training, and in near zero-shot conditions, our single proposed model can perform four tasks: controlled paraphrase generation in both languages and controlled machine translation in both language directions. To evaluate these tasks quantitatively, we create three novel evaluation datasets. |
Mingda Chen; Sam Wiseman; Kevin Gimpel; | arxiv-cs.CL | 2020-10-12 |
| 470 | Towards Machine Translation For The Kurdish Language Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we are addressing the main issues in creating a machine translation system for the Kurdish language, with a focus on the Sorani dialect. |
Sina Ahmadi; Mariam Masoud; | arxiv-cs.CL | 2020-10-12 |
| 471 | Improving Text Generation With Student-Forcing Optimal Transport Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To reduce this gap between training and testing, we propose using optimal transport (OT) to match the sequences generated in these two modes. |
GUOYIN WANG et. al. | arxiv-cs.CL | 2020-10-12 |
| 472 | Gender Coreference And Bias Evaluation At WMT 2020 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our work presents the largest evidence for the phenomenon in more than 19 systems submitted to the WMT over four diverse target languages: Czech, German, Polish, and Russian. |
Tom Kocmi; Tomasz Limisiewicz; Gabriel Stanovsky; | arxiv-cs.CL | 2020-10-12 |
| 473 | Fairseq S2T: Fast Speech-to-Text Modeling With Fairseq IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) modeling tasks such as end-to-end speech recognition and speech-to-text translation. |
CHANGHAN WANG et. al. | arxiv-cs.CL | 2020-10-11 |
| 474 | Detecting Foodborne Illness Complaints In Multiple Languages Using English Annotations Only Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate the benefits of our approach through extensive experiments with Yelp restaurant reviews in seven languages. |
Ziyi Liu; Giannis Karamanolakis; Daniel Hsu; Luis Gravano; | arxiv-cs.CL | 2020-10-11 |
| 475 | Lexically Cohesive Neural Machine Translation With Copy Mechanism Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We employ a copy mechanism into a context-aware neural machine translation model to allow copying words from previous translation outputs. |
Vipul Mishra; Chenhui Chu; Yuki Arase; | arxiv-cs.CL | 2020-10-11 |
| 476 | Addressing Exposure Bias With Document Minimum Risk Training: Cambridge At The WMT20 Biomedical Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This can result in poor behaviour during inference if the model learns to neglect the source sentence. |
Danielle Saunders; Bill Byrne; | arxiv-cs.CL | 2020-10-11 |
| 477 | Neural Machine Translation Doesn’t Translate Gender Coreference Right Unless You Make It Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose schemes for incorporating explicit word-level gender inflection tags into NMT. |
Danielle Saunders; Rosie Sallis; Bill Byrne; | arxiv-cs.CL | 2020-10-11 |
| 478 | Machine Translation Of Mathematical Text Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We have trained a Transformer-based translator model, using OpenNMT, on a combined corpus containing a small proportion of domain-specific sentences. |
Aditya Ohri; Tanya Schmah; | arxiv-cs.CL | 2020-10-11 |
| 479 | SJTU-NICT’s Supervised And Unsupervised Neural Machine Translation Systems For The WMT20 News Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduced our joint team SJTU-NICT ‘s participation in the WMT 2020 machine translation shared task. |
ZUCHAO LI et. al. | arxiv-cs.CL | 2020-10-10 |
| 480 | Localizing Open-Ontology QA Semantic Parsers In A Day Using Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Semantic Parser Localizer (SPL), a toolkit that leverages Neural Machine Translation (NMT) systems to localize a semantic parser for a new language. |
Mehrad Moradshahi. Giovanni Campagna; Sina J. Semnani; Silei Xu; Monica S. Lam; | arxiv-cs.CL | 2020-10-10 |
| 481 | Word Level Language Identification In English Telugu Code Mixed Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a study of various models – Nave Bayes Classifier, Random Forest Classifier, Conditional Random Field (CRF), and Hidden Markov Model (HMM) for Language Identification in English – Telugu Code Mixed Data. |
Sunil Gundapu; Radhika Mamidi; | arxiv-cs.CL | 2020-10-09 |
| 482 | Recursive Top-Down Production For Sentence Generation With Latent Trees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we present a dynamic programming algorithm that marginalises over latent binary tree structures with $N$ leaves, allowing us to compute the likelihood of a sequence of $N$ tokens under a latent tree model, which we maximise to train a recursive neural function. |
Shawn Tan; Yikang Shen; Timothy J. O’Donnell; Alessandro Sordoni; Aaron Courville; | arxiv-cs.CL | 2020-10-09 |
| 483 | Learning To Evaluate Translation Beyond English: BLEURT Submissions To The WMT Metrics 2020 Shared Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our contribution to the WMT 2020 Metrics Shared Task, the main benchmark for automatic evaluation of translation. |
THIBAULT SELLAM et. al. | arxiv-cs.CL | 2020-10-08 |
| 484 | PyMT5: Multi-mode Translation Of Natural Language And Python Code With Transformers IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an analysis and modeling effort of a large-scale parallel corpus of 26 million Python methods and 7.7 million method-docstring pairs, demonstrating that for docstring and method generation, PyMT5 outperforms similarly-sized auto-regressive language models (GPT2) which were English pre-trained or randomly initialized. |
Colin B. Clement; Dawn Drain; Jonathan Timcheck; Alexey Svyatkovskiy; Neel Sundaresan; | arxiv-cs.LG | 2020-10-07 |
| 485 | Why Skip If You Can Combine: A Simple Knowledge Distillation Technique For Intermediate Layers IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we target low-resource settings and evaluate our translation engines for Portuguese–English, Turkish–English, and English–German directions. |
Yimeng Wu; Peyman Passban; Mehdi Rezagholizade; Qun Liu; | arxiv-cs.CL | 2020-10-06 |
| 486 | An Empirical Study Of Tokenization Strategies For Various Korean NLP Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we test several tokenization strategies in order to answer our primary research question, that is, What is the best tokenization strategy for Korean NLP tasks? |
Kyubyong Park; Joohong Lee; Seongbo Jang; Dawoon Jung; | arxiv-cs.CL | 2020-10-06 |
| 487 | Data Rejuvenation: Exploiting Inactive Training Examples For Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore to identify the inactive training examples which contribute less to the model performance, and show that the existence of inactive examples depends on the data distribution. |
WENXIANG JIAO et. al. | arxiv-cs.CL | 2020-10-06 |
| 488 | Leveraging Multilingual News Websites For Building A Kurdish Parallel Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In an attempt to create parallel corpora for the Kurdish language, in this paper, we describe our approach in retrieving potentially-alignable news articles from multi-language websites and manually align them across dialects and languages based on lexical similarity and transliteration of scripts. We present a corpus containing 12,327 translation pairs in the two major dialects of Kurdish, Sorani and Kurmanji. |
Sina Ahmadi; Hossein Hassani; Daban Q. Jaff; | arxiv-cs.CL | 2020-10-04 |
| 489 | Syntax Representation In Word Embeddings And Neural Networks — A Survey Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe which pre-trained models and representations of language are best suited for transfer to syntactic tasks. |
Tomasz Limisiewicz; David Mareček; | arxiv-cs.CL | 2020-10-02 |
| 490 | WeChat Neural Machine Translation Systems For WMT20 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In our experiments, we employ data selection, several synthetic data generation approaches (i.e., back-translation, knowledge distillation, and iterative in-domain knowledge transfer), advanced finetuning approaches and self-bleu based model ensemble. |
FANDONG MENG et. al. | arxiv-cs.CL | 2020-10-01 |
| 491 | Nearest Neighbor Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce $k$-nearest-neighbor machine translation ($k$NN-MT), which predicts tokens with a nearest neighbor classifier over a large datastore of cached examples, using representations from a neural translation model for similarity search. |
Urvashi Khandelwal; Angela Fan; Dan Jurafsky; Luke Zettlemoyer; Mike Lewis; | arxiv-cs.CL | 2020-10-01 |
| 492 | A Simple But Tough-to-Beat Data Augmentation Approach For Natural Language Understanding And Generation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a set of simple yet effective data augmentation strategies dubbed cutoff, where part of the information within an input sentence is erased to yield its restricted views (during the fine-tuning stage). |
Dinghan Shen; Mingzhi Zheng; Yelong Shen; Yanru Qu; Weizhu Chen; | arxiv-cs.CL | 2020-09-29 |
| 493 | Aspects Of Terminological And Named Entity Knowledge Within Rule-Based Machine Translation Models For Under-Resourced Neural Machine Translation Scenarios Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe different approaches to leverage the information contained in rule-based machine translation systems to improve a corpus-based one, namely, a neural machine translation model, with a focus on a low-resource scenario. |
DANIEL TORREGROSA et. al. | arxiv-cs.CL | 2020-09-28 |
| 494 | Automatic Arabic Dialect Identification Systems For Written Texts: A Survey Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a comprehensive survey of Arabic dialect identification research in written texts. |
Maha J. Althobaiti; | arxiv-cs.CL | 2020-09-26 |
| 495 | XTE: Explainable Text Entailment Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce XTE – Explainable Text Entailment – a novel composite approach for recognizing text entailment which analyzes the entailment pair to decide whether it must be resolved syntactically or semantically. |
Vivian S. Silva; André Freitas; Siegfried Handschuh; | arxiv-cs.CL | 2020-09-25 |
| 496 | Harnessing Multilinguality in Unsupervised Machine Translation for Rare Languages IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that multilinguality is critical to making unsupervised systems practical for low-resource settings. |
Xavier Garcia; Aditya Siddhant; Orhan Firat; Ankur P. Parikh; | arxiv-cs.CL | 2020-09-23 |
| 497 | Listen, Understand and Translate: Triple Supervision Decouples End-to-end Speech-to-text Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Listen-Understand-Translate, (LUT), a unified framework with triple supervision signals to decouple the end-to-end speech-to-text translation task. |
QIANQIAN DONG et. al. | arxiv-cs.CL | 2020-09-21 |
| 498 | Consecutive Decoding for Speech-to-text Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To reduce the learning difficulty, we propose COnSecutive Transcription and Translation (COSTT), an integral approach for speech-to-text translation. |
QIANQIAN DONG et. al. | arxiv-cs.CL | 2020-09-21 |
| 499 | Softmax Tempering For Training Neural Machine Translation Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose to divide the logits by a temperature coefficient, prior to applying softmax, during training. |
Raj Dabre; Atsushi Fujita; | arxiv-cs.CL | 2020-09-20 |
| 500 | Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use both marginal energy models (over target sentence) and joint energy models (over both source and target sentences). |
SUMANTA BHATTACHARYYA et. al. | arxiv-cs.CL | 2020-09-19 |
| 501 | Towards Computational Linguistics In Minangkabau Language: Studies On Sentiment Analysis And Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we release two Minangkabau corpora: sentiment analysis and machine translation that are harvested and constructed from Twitter and Wikipedia. |
Fajri Koto; Ikhwan Koto; | arxiv-cs.CL | 2020-09-19 |
| 502 | Computer Assisted Translation With Neural Quality Estimation And Automatic Post-Editing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an end-to-end deep learning framework of the quality estimation and automatic post-editing of the machine translation output. |
JIAYI WANG et. al. | arxiv-cs.CL | 2020-09-18 |
| 503 | Unsupervised Parallel Corpus Mining On Web Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a pipeline to mine the parallel corpus from the Internet in an unsupervised manner. |
Guokun Lai; Zihang Dai; Yiming Yang; | arxiv-cs.CL | 2020-09-17 |
| 504 | Graph-to-Sequence Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In detail, we propose a graph-based SAN-based NMT model called Graph-Transformer by capturing information of subgraphs of different orders in every layers. |
Sufeng Duan; Hai Zhao; Rui Wang; | arxiv-cs.CL | 2020-09-16 |
| 505 | Multilingual Music Genre Embeddings For Effective Cross-Lingual Music Item Annotation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, by learning multilingual music genre embeddings, we enable cross-lingual music genre translation without relying on a parallel corpus. We publicly release the new multilingual data and code. |
Elena V. Epure; Guillaume Salha; Romain Hennequin; | arxiv-cs.CL | 2020-09-16 |
| 506 | Simultaneous Machine Translation With Visual Context Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we seek to understand whether the addition of visual information can compensate for the missing source context. |
OZAN CAGLAYAN et. al. | arxiv-cs.CL | 2020-09-15 |
| 507 | Combining Word And Character Vector Representation On Neural Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes combinations of word vector representation and character vector representation in English-Indonesian neural machine translation (NMT). |
K. M. Shahih; Ayu Purwarianti; | arxiv-cs.CL | 2020-09-13 |
| 508 | Central Yup’ik And Machine Translation Of Low-Resource Polysynthetic Languages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We trained a seq2seq neural machine translation model with attention to translate Yup’ik input into English. |
Christopher Liu; Laura Dominé; Kevin Chavez; Richard Socher; | arxiv-cs.CL | 2020-09-08 |
| 509 | Why Not Simply Translate? A First Swedish Evaluation Benchmark For Semantic Similarity Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents the first Swedish evaluation benchmark for textual semantic similarity. |
Tim Isbister; Magnus Sahlgren; | arxiv-cs.CL | 2020-09-07 |
| 510 | Modeling Global Body Configurations In American Sign Language Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main contributions of this paper are |
Nicholas Wilkins; Beck Cordes Galbraith; Ifeoma Nwogu; | arxiv-cs.CV | 2020-09-03 |
| 511 | Unsupervised Translation Via Hierarchical Anchoring: Functional Mapping Of Places Across Cities Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We address this problem by proposing an unsupervised translation method that translates embeddings by exploiting common hierarchical structures that exist across imbalanced domains. |
Takahiro Yabe; Kota Tsubouchi; Toru Shimizu; Yoshihide Sekimoto; Satish V. Ukkusuri; | kdd | 2020-08-21 |
| 512 | Lite Training Strategies For Portuguese-English And English-Portuguese Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate the use of pre-trained models, such as T5 for Portuguese-English and English-Portuguese translation tasks using low-cost hardware. |
Alexandre Lopes; Rodrigo Nogueira; Roberto Lotufo; Helio Pedrini; | arxiv-cs.CL | 2020-08-20 |
| 513 | Very Deep Transformers For Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We explore the application of very deep Transformer models for Neural Machine Translation (NMT). |
Xiaodong Liu; Kevin Duh; Liyuan Liu; Jianfeng Gao; | arxiv-cs.CL | 2020-08-18 |
| 514 | Approaching Neural Chinese Word Segmentation As A Low-Resource Machine Translation Task Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we apply the best practices from low-resource neural machine translation to Chinese word segmentation. |
Pinzhen Chen; Kenneth Heafield; | arxiv-cs.CL | 2020-08-12 |
| 515 | A Parallel Evaluation Data Set Of Software Documentation With Document Structure Annotation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide insights into the origin and creation, the particularities and characteristics of the data set as well as machine translation results. |
Bianka Buschbeck; Miriam Exel; | arxiv-cs.CL | 2020-08-11 |
| 516 | Paraphrase Generation As Zero-Shot Multilingual Translation: Disentangling Semantic Similarity From Lexical And Syntactic Diversity IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a simple paraphrase generation algorithm which discourages the production of n-grams that are present in the input. |
Brian Thompson; Matt Post; | arxiv-cs.CL | 2020-08-11 |
| 517 | A Multilingual Neural Machine Translation Model For Biomedical Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We also release a test set of biomedical text for Korean-English. |
Alexandre Bérard; Zae Myung Kim; Vassilina Nikoulina; Eunjeong L. Park; Matthias Gallé; | arxiv-cs.CL | 2020-08-06 |
| 518 | Contextualized Translation Of Automatically Segmented Speech Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, instead, we address the issue in the model, making it more robust to a different, potentially sub-optimal segmentation. |
Marco Gaido; Mattia Antonino Di Gangi; Matteo Negri; Mauro Cettolo; Marco Turchi; | arxiv-cs.CL | 2020-08-05 |
| 519 | Designing The Business Conversation Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to boost the machine translation quality of conversational texts by introducing a newly constructed Japanese-English business conversation parallel corpus. |
Matīss Rikters; Ryokan Ri; Tong Li; Toshiaki Nakazawa; | arxiv-cs.CL | 2020-08-05 |
| 520 | A Survey Of Orthographic Information In Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe previous work in this area, discussing what underlying assumptions were made, and showing how orthographic knowledge improves the performance of machine translation of under-resourced languages. |
Bharathi Raja Chakravarthi; Priya Rani; Mihael Arcan; John P. McCrae; | arxiv-cs.CL | 2020-08-04 |
| 521 | On Learning Universal Representations Across Languages IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend these approaches to learn sentence-level representations and show the effectiveness on cross-lingual understanding and generation. |
XIANGPENG WEI et. al. | arxiv-cs.CL | 2020-07-31 |
| 522 | Preparation Of Sentiment Tagged Parallel Corpus And Testing Its Effect On Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the current work, we explore the enrichment in the machine translation output when the training parallel corpus is augmented with the introduction of sentiment analysis. |
Sainik Kumar Mahata; Amrita Chandra; Dipankar Das; Sivaji Bandyopadhyay; | arxiv-cs.CL | 2020-07-28 |
| 523 | A System For Worldwide COVID-19 Information Aggregation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We build a system for worldwide COVID-19 information aggregation containing reliable articles from 10 regions in 7 languages sorted by topics. |
AKIKO AIZAWA et. al. | arxiv-cs.CL | 2020-07-27 |
| 524 | Searching The Web For Cross-lingual Parallel Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce techniques for searching for cross-lingual parallel data based on language, content, and other metadata. |
Ahmed El-Kishky; Philipp Koehn; Holger Schwenk; | sigir | 2020-07-25 |
| 525 | JUNLP@SemEval-2020 Task 9:Sentiment Analysis Of Hindi-English Code Mixed Data Using Grid Search Cross Validation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on working out a plausible solution to the domain of Code-Mixed Sentiment Analysis. |
Avishek Garain; Sainik Kumar Mahata; Dipankar Das; | arxiv-cs.CL | 2020-07-24 |
| 526 | Bridging The Gap Between Training And Inference For Neural Machine Translation (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address these issues by sampling context words not only from the ground truth sequence but also from the predicted sequence during training. |
Wen Zhang; Yang Feng; Qun Liu; | ijcai | 2020-07-21 |
| 527 | Knowledge Graphs Enhanced Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve the translation quality of these entities, in this paper we propose a novel KGs enhanced NMT method. |
Yang Zhao; Jiajun Zhang; Yu Zhou; Chengqing Zong; | ijcai | 2020-07-21 |
| 528 | Modeling Voting For System Combination In Machine Translation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an approach to modeling voting for system combination in machine translation. |
XUANCHENG HUANG et. al. | ijcai | 2020-07-21 |
| 529 | Efficient Context-Aware Neural Machine Translation With Layer-Wise Weighting And Input-Aware Gating Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to make the most of layers pre-trained on sentence-level data in contextual representation learning, reusing representations from the sentence-level Transformer and significantly reducing the cost of incorporating contexts in translation. |
Hongfei Xu; Deyi Xiong; Josef van Genabith; Qiuhui Liu; | ijcai | 2020-07-21 |
| 530 | Emoji-Powered Representation Learning For Cross-Lingual Sentiment Classification (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we employ emojis, which are widely available in many languages, as a new channel to learn both the cross-language and the language-specific sentiment patterns. |
ZHENPENG CHEN et. al. | ijcai | 2020-07-21 |
| 531 | Lexical-Constraint-Aware Neural Machine Translation Via Data Augmentation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In response to these problems, we present a conceptually simple and empirically effective data augmentation approach in lexical constrained neural machine translation. |
Guanhua Chen; Yun Chen; Yong Wang; Victor O.K. Li; | ijcai | 2020-07-21 |
| 532 | Voice@SRIB At SemEval-2020 Task 9 And 12: Stacked Ensembling Method For Sentiment And Offensiveness Detection In Social Media Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe different models we used, using the external dataset to train embeddings, ensembling methods for Sentimix, and OffensEval tasks. |
Abhishek Singh; Surya Pratap Singh Parmar; | arxiv-cs.CL | 2020-07-20 |
| 533 | CoVoST 2 And Massively Multilingual Speech-to-Text Translation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Speech translation has recently become an increasingly popular topic of research, partly due to the development of benchmark datasets. Nevertheless, current datasets cover a … |
Changhan Wang; Anne Wu; Juan Pino; | arxiv-cs.CL | 2020-07-20 |
| 534 | A Multilingual Parallel Corpora Collection Effort For Indian Lang |