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Towards EMG-to-Speech with a Necklace Form Factor

Authors :
Wu, Peter
Kaveh, Ryan
Nautiyal, Raghav
Zhang, Christine
Guo, Albert
Kachinthaya, Anvitha
Mishra, Tavish
Yu, Bohan
Black, Alan W
Muller, Rikky
Anumanchipalli, Gopala Krishna
Publication Year :
2024

Abstract

Electrodes for decoding speech from electromyography (EMG) are typically placed on the face, requiring adhesives that are inconvenient and skin-irritating if used regularly. We explore a different device form factor, where dry electrodes are placed around the neck instead. 11-word, multi-speaker voiced EMG classifiers trained on data recorded with this device achieve 92.7% accuracy. Ablation studies reveal the importance of having more than two electrodes on the neck, and phonological analyses reveal similar classification confusions between neck-only and neck-and-face form factors. Finally, speech-EMG correlation experiments demonstrate a linear relationship between many EMG spectrogram frequency bins and self-supervised speech representation dimensions.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.21345
Document Type :
Working Paper