wu24k@interspeech_2024@ISCA

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#1 Towards EMG-to-Speech with Necklace Form Factor [PDF] [Copy] [Kimi] [REL]

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

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 frequencies and self-supervised speech representation dimensions.