Laryngoscope investigative otolaryngology · 2026
Noninvasive Speech Restoration After Total Laryngectomy Using Surface Electromyography: Pilot Study.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Kaushal Naresh K, Comstock Daniel C, Belafsky Peter C, Ramirez-Aristizabal Adolfo, Miller Lee M
Аннотация
OBJECTIVE: To demonstrate the feasibility of restoring intelligible, own-voice speech after total laryngectomy using noninvasive surface electromyography.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
LEVEL OF EVIDENCE: 4.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
LEVEL OF EVIDENCE: 4.