PAPER DIGEST
Most Influential MOBICOM 2019 Paper · 2026-03 edition

SignSpeaker: A Real-time, High-Precision SmartWatch-based Sign Language Translator

Jiahui Hou, Xiang-Yang Li, Peide Zhu, Zefan Wang, Yu Wang, Jianwei Qian, Panlong Yang

Venue
International Conference on Mobile Computing and Networking (MOBICOM) 2019
Recognition
Most Influential MOBICOM 2019 Paper (Rank No. 7)
Edition
2026-03
Impact factor
4
Certificate ID
595f5e76b18fb4c1

Abstract

Sign language is a natural and fully-formed communication method for deaf or hearing-impaired people. Unfortunately, most of the state-of-the-art sign recognition technologies are limited by either high energy consumption or expensive device costs and have a difficult time providing a real-time service in a daily-life environment. Inspired by previous works on motion detection with wearable devices, we propose Sign Speaker - a real-time, robust, and user-friendly American sign language recognition (ASLR) system with affordable and portable commodity mobile devices. SignSpeaker is deployed on a smartwatch along with a smartphone; the smartwatch collects the sign signals and the smartphone outputs translation through an inbuilt loudspeaker. We implement a prototype system and run a series of experiments that demonstrate the promising performance of our system. For example, the average translation time is approximately $1.1$ seconds for a sentence with eleven words. The average detection ratio and reliability of sign recognition are 99.2% and 99.5%, respectively. The average word error rate of continuous sentence recognition is 1.04% on average.

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