Noninvasive Speech Restoration After Total Laryngectomy Using Surface Electromyography: Pilot Study.

Authors

Naresh K Kaushal, Daniel C Comstock, Peter C Belafsky, Adolfo Ramirez-Aristizabal, Lee M Miller

Published in

Laryngoscope investigative otolaryngology. Volume 11. Issue 5. Pages e70559. Epub Sep 02, 2026.

Abstract

To demonstrate the feasibility of restoring intelligible, own-voice speech after total laryngectomy using noninvasive surface electromyography.
One post-laryngectomy patient and one healthy reference speaker silently articulated a closed-vocabulary corpus of 499 dates and times while surface electromyographic (sEMG) signals were recorded from a 20-electrode face, jaw, and neck montage. A decoder mapped sEMG into speaker-independent speech tokens, which a public token-to-speech stack converted into audible speech; for the patient, the output was re-rendered in his own pre-surgical voice using approximately 8 min of audio recorded before surgery. A per-subject procedure identified a reduced electrode subset, and performance was evaluated by five human listeners.
The system produced intelligible speech in the patient's own pre-surgical voice. Mean word error rate by human listeners was 20.2% (95% CI 11.0%-31.5%) for the patient and 14.9% (6.8%-24.9%) for the reference speaker. Electrode-selection analysis indicated that roughly half of the recorded electrodes captured 95% of the multi-channel signal (9 of 20 for the patient, 11 of 18 for the reference), supporting more compact hardware. Single-trial recordings showed coordinated muscle activity tracking each silently articulated word despite the absence of phonation.
Noninvasive sEMG-based speech restoration is feasible after total laryngectomy. By decoding muscle activity into a speaker-independent representation, the approach sidesteps the absence of post-surgical own-voice audio and remains applicable to patients unable to phonate. Unlike existing alternatives (electrolarynx, esophageal speech, tracheoesophageal puncture), it can also restore the patient's own pre-surgical voice, offering a high-performing, low-complication path toward clinical use.
4.

PMID:
42694022
Bibliographic data and abstract were imported from PubMed on 04 Sep 2026.

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