SilentSpeller: Towards mobile, hands-free, silent speech text entry using electropalatography

要旨

Speech is inappropriate in many situations, limiting when voice control can be used. Most unvoiced speech text entry systems can not be used while on-the-go due to movement artifacts. Using a dental retainer with capacitive touch sensors, SilentSpeller tracks tongue movement, enabling users to type by spelling words without voicing. SilentSpeller achieves an average 97% character accuracy in offline isolated word testing on a 1164-word dictionary. Walking has little effect on accuracy; average offline character accuracy was roughly equivalent on 107 phrases entered while walking (97.5%) or seated (96.5%). To demonstrate extensibility, the system was tested on 100 unseen words, leading to an average 94% accuracy. Live text entry speeds for seven participants averaged 37 words per minute at 87% accuracy. Comparing silent spelling to current practice suggests that SilentSpeller may be a viable alternative for silent mobile text entry.

著者
Naoki Kimura
The University of Tokyo, Bunkyo, Tokyo, Japan
Tan Gemicioglu
Georgia Institute of Technology, Atlanta, Georgia, United States
Jonathan Womack
Georgia Institute of Technology, Atlanta, Georgia, United States
Yuhui Zhao
Georgia Institute of Technology, Atlanta, Georgia, United States
Richard Li
University of Washington, Seattle, Washington, United States
Abdelkareem Bedri
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Zixiong Su
The University of Tokyo, Tokyo, Japan
Alex Olwal
Google Inc., Mountain View, California, United States
Jun Rekimoto
The University of Tokyo, Tokyo, Japan
Thad Starner
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3502015

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Sensing

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5 件の発表
2022-05-05 01:15:00
2022-05-05 02:30:00