Surface Electromyography-Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech.

ABSTRACT: Purpose This study aimed to evaluate a novel communication system designed to translate surface electromyographic (sEMG) signals from articulatory muscles into speech using a personalized, digital voice. The system was evaluated for word recognition, prosodic classification, and listener perception of synthesized speech. Method sEMG signals were recorded from the face and neck as speakers with (n = 4) and without (n = 4) laryngectomy subvocally recited (silently mouthed) a speech corpus comprising 750 phrases (150 phrases with variable phrase-level stress). Corpus tokens were then translated into speech via personalized voice synthesis (n = 8 synthetic voices) and compared against phrases produced by each speaker when using their typical mode of communication (n

SUBMITTER: Vojtech JM 

PROVIDER: S-EPMC8740708 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature