2 papers
cs.LG2026
Multi-Subject Pretraining Enables Short-Calibration Personalization for Closed-Corpus Surface EMG Speech Decoding
Chenqian Le, Beatrice Fumagalli, Yasamin Esmaeili +5
Surface electromyography (sEMG)-based silent speech interfaces are limited by cross-user variability and calibration burden. We study a limited-data setting in which each of 27 spe…
cs.SD2026
Comparison of sEMG Encoding Accuracy Across Speech Modes Using Articulatory and Phoneme Features
Chenqian Le, Ruisi Li, Beatrice Fumagalli +6
We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four s…