ArticleJournal of speech, language, and hearing research : JSLHR2023
MagTrack: A Wearable Tongue Motion Tracking System for Silent Speech Interfaces.
Article in Journal of speech, language, and hearing research : JSLHR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- A multimodal speech-production dataset with time-aligned articulography, EEG, audio, and vocal-tract anatomy.Scientific data · 2026Article
- An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.Perspectives of the ASHA special interest groups · 2025Article
- Bioinspired Artificial Intelligence Applications 2023.Biomimetics (Basel, Switzerland) · 2024Article
- Improving Reliability of Magnetic Localization Using Input Space Transformation.IEEE sensors journal · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
purposeCurrent electromagnetic tongue tracking devices are not amenable for daily use and thus not suitable for silent speech interface and other applications. We have recently developed MagTrack, a novel wearable electromagnetic articulograph tongue tracking device. This study aimed to validate MagTrack for potential silent speech interface applications.
methodWe conducted two experiments: (a) classification of eight isolated vowels in consonant-vowel-consonant form and (b) continuous silent speech recognition. In these experiments, we used data from healthy adult speakers collected with MagTrack. The performance of vowel classification was measured by accuracies. The continuous silent speech recognition was measured by phoneme error rates. The performance was then compared with results using data collected with commercial electromagnetic articulograph in a prior study.
resultsThe isolated vowel classification using MagTrack achieved an average accuracy of 89.74% when leveraging all MagTrack signals (
conclusionsMagTrack showed comparable results with the commercial electromagnetic articulograph when using the same localized information. Adding raw magnetic signals would improve the performance of MagTrack. Our preliminary testing demonstrated the potential for silent speech interface as a lightweight wearable device. This work also lays the foundation to support MagTrack's potential for other applications including visual feedback-based speech therapy and second language learning.
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