Skip to main navigation Skip to search Skip to main content

Leveraging earables for unvoiced command recognition

  • Tanmay Srivastava
  • , Prerna Khanna
  • , Shijia Pan
  • , Phuc Nguyen
  • , Shubham Jain
  • Stony Brook University
  • University of California Merced
  • University of Texas at Arlington

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We demonstrate an ear-worn technology that recognizes unvoiced human commands by tracking jaw motion. The ear-worn system is designed to achieve continual unvoiced command recognition for robust human-computer interaction (HCI) applications. First, the system reliably extracts the jaw motion signals buried under the noise caused by head motion, walking, and other motion artifacts to track single secondary voice articulator (i.e., word). Then, learning from linguistics and human speech anatomy, we design a novel algorithm that localizes the phonemes in the command, and reconstructs the word. We evaluate the proposed system in real-world experiments with 15 volunteers. Our preliminary results show that the proposed system obtains a word recognition accuracy of 95.6% in noise-free conditions and 93.2% and 91.6%, while head nodding and walking.

Original languageEnglish
Title of host publicationMobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services
PublisherAssociation for Computing Machinery, Inc
Pages622-623
Number of pages2
ISBN (Electronic)9781450391856
DOIs
StatePublished - Jun 27 2022
Event20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022 - Portland, United States
Duration: Jun 27 2022Jul 1 2022

Publication series

NameMobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services

Conference

Conference20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022
Country/TerritoryUnited States
CityPortland
Period06/27/2207/1/22

Keywords

  • earable
  • IMU sensing
  • unvoiced speech recognition
  • wearable devices

Fingerprint

Dive into the research topics of 'Leveraging earables for unvoiced command recognition'. Together they form a unique fingerprint.

Cite this