Micro-Gesture Recognition of Tongue via Bone Conduction Sound
Authors: 
Shogo Tomaru, Ken Takaki, Hiroaki Murakami, Damyon Kim, Koya Narumi, Mitsuhiro Kamezaki, 
Yoshihiro KawaharaAuthors Info & Claims
Article No.: 96, Pages 1 - 3
Abstract
We propose a hands-free and less perceptible gesture sensing method of the tongue by capturing the bone conduction sound generated when the tongue rubs the teeth. The sound is captured by the bone conduction microphones attached behind the ears. In this work, we show that tongue slide, snap, and teeth click gestures can be classified using the decision tree algorithm, which focuses on the characteristics in the sound spectrogram. We conducted a preliminary experiment to verify that input methods for mouth microgesture devices using bone conduction can be expanded from only teeth to teeth and tongue gestures without any additional obtrusive sensors. The evaluation revealed that our method achieved a classification accuracy of 82.7% with user-specific parameter adjustment.
References
[1]
Victor Chen, Xuhai Xu, Richard Li, Yuanchun Shi, Shwetak Patel, and Yuntao Wang. 2021. Understanding the Design Space of Mouth Microgestures. In Proceedings of the 2021 ACM Designing Interactive Systems Conference (Virtual Event, USA) (DIS ’21). Association for Computing Machinery, New York, NY, USA, 1068–1081. https://doi.org/10.1145/3461778.3462004
[2]
Jingyuan Cheng, Ayano Okoso, Kai Kunze, Niels Henze, Albrecht Schmidt, Paul Lukowicz, and Koichi Kise. 2014. On the Tip of My Tongue: A Non-Invasive Pressure-Based Tongue Interface. In Proceedings of the 5th Augmented Human International Conference (Kobe, Japan) (AH ’14). Association for Computing Machinery, New York, NY, USA, Article 12, 4 pages. https://doi.org/10.1145/2582051.2582063
[3]
B. Denby, T. Schultz, K. Honda, T. Hueber, J.M. Gilbert, and J.S. Brumberg. 2010. Silent speech interfaces. Speech Communication 52, 4 (2010), 270–287. https://doi.org/10.1016/j.specom.2009.08.002
[4]
Morten Lund Dybdal, Javier San Agustin, and John Paulin Hansen. 2012. Gaze Input for Mobile Devices by Dwell and Gestures. In Proceedings of the Symposium on Eye Tracking Research and Applications (Santa Barbara, California) (ETRA ’12). Association for Computing Machinery, New York, NY, USA, 225–228. https://doi.org/10.1145/2168556.2168601
[5]
Susumu Harada, James A. Landay, Jonathan Malkin, Xiao Li, and Jeff A. Bilmes. 2006. The Vocal Joystick: Evaluation of Voice-Based Cursor Control Techniques. In Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility (Portland, Oregon, USA) (Assets ’06). Association for Computing Machinery, New York, NY, USA, 197–204. https://doi.org/10.1145/1168987.1169021
[6]
Richard Li, Jason Wu, and Thad Starner. 2019. TongueBoard: An Oral Interface for Subtle Input. In Proceedings of the 10th Augmented Human International Conference 2019 (Reims, France) (AH2019). Association for Computing Machinery, New York, NY, USA, Article 1, 9 pages. https://doi.org/10.1145/3311823.3311831
[7]
Phuc Nguyen, Nam Bui, Anh Nguyen, Hoang Truong, Abhijit Suresh, Matt Whitlock, Duy Pham, Thang Dinh, and Tam Vu. 2018. TYTH-Typing On Your Teeth: Tongue-Teeth Localization for Human-Computer Interface. In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services (Munich, Germany) (MobiSys ’18). Association for Computing Machinery, New York, NY, USA, 269–282. https://doi.org/10.1145/3210240.3210322
[8]
Jay Prakash, Zhijian Yang, Yu-Lin Wei, Haitham Hassanieh, and Romit Roy Choudhury. 2020. EarSense: Earphones as a Teeth Activity Sensor. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking (London, United Kingdom) (MobiCom ’20). Association for Computing Machinery, New York, NY, USA, Article 40, 13 pages. https://doi.org/10.1145/3372224.3419197
[9]
Himanshu Sahni, Abdelkareem Bedri, Gabriel Reyes, Pavleen Thukral, Zehua Guo, Thad Starner, and Maysam Ghovanloo. 2014. The Tongue and Ear Interface: A Wearable System for Silent Speech Recognition. In Proceedings of the 2014 ACM International Symposium on Wearable Computers (Seattle, Washington) (ISWC ’14). Association for Computing Machinery, New York, NY, USA, 47–54. https://doi.org/10.1145/2634317.2634322
[10]
T. Scott Saponas, Daniel Kelly, Babak A. Parviz, and Desney S. Tan. 2009. Optically Sensing Tongue Gestures for Computer Input. In Proceedings of the 22nd Annual ACM Symposium on User Interface Software and Technology (Victoria, BC, Canada) (UIST ’09). Association for Computing Machinery, New York, NY, USA, 177–180. https://doi.org/10.1145/1622176.1622209
[11]
Tomás Vega Gálvez, Shardul Sapkota, Alexandru Dancu, and Pattie Maes. 2019. Byte.It: Discreet Teeth Gestures for Mobile Device Interaction. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI EA ’19). Association for Computing Machinery, New York, NY, USA, 1–6. https://doi.org/10.1145/3290607.3312925
[12]
Qiao Zhang, Shyamnath Gollakota, Ben Taskar, and Raj P.N. Rao. 2014. Non-Intrusive Tongue Machine Interface. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Toronto, Ontario, Canada) (CHI ’14). Association for Computing Machinery, New York, NY, USA, 2555–2558. https://doi.org/10.1145/2556288.2556981
Index Terms
- Micro-Gesture Recognition of Tongue via Bone Conduction Sound
Recommendations
TongueTap: Multimodal Tongue Gesture Recognition with Head-Worn Devices
ICMI '23: Proceedings of the 25th International Conference on Multimodal InteractionMouth-based interfaces are a promising new approach enabling silent, hands-free and eyes-free interaction with wearable devices. However, interfaces sensing mouth movements are traditionally custom-designed and placed near or within the mouth. TongueTap ...
Spectrum Analysis of Bone-conducted Speech: A Study Based on Intelligibility Scoring
ISAIMS '20: Proceedings of the 1st International Symposium on Artificial Intelligence in Medical SciencesThe optimization of bone conduction speech in Mandarin Chinese is still a problem. In this paper, after recording the bone-conducted syllables of the head (vertex, temple, cheek, larynx), then the subjects are told to score the speech intelligibility, ...
Bone-and air-conduction speech combination method for speaker recognition
In this paper, first, we report speaker recognition performance using bone-conduction speech based on an i-vector-based speaker recognition system, which is the current state-of-the-art method. In addition, we propose three speaker recognition methods ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2024
394 pages
Copyright © 2024 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 October 2024
Check for updates
Author Tags
Qualifiers
- Poster
- Research
- Refereed limited
Funding Sources
- This is a joint research project with a private company.
Conference
UIST '24: The 37th Annual ACM Symposium on User Interface Software and Technology
October 13 - 16, 2024
PA, Pittsburgh, USA
Acceptance Rates
Overall Acceptance Rate 355 of 1,733 submissions, 20%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 88Total Downloads
- Downloads (Last 12 months)88
- Downloads (Last 6 weeks)88
Reflects downloads up to 23 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format