ERIC Number: EJ1307740
Record Type: Journal
Publication Date: 2021-Jun
Pages: 20
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1092-4388
EISSN: N/A
Surface Electromyography-Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech
Vojtech, Jennifer M.; Chan, Michael D.; Shiwani, Bhawna; Roy, Serge H.; Heaton, James T.; Meltzner, Geoffrey S.; Contessa, Paola; De Luca, Gianluca; Patel, Rupal; Kline, Joshua C.
Journal of Speech, Language, and Hearing Research, v64 n6 spec iss p2134-2153 Jun 2021
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 = 4 natural voices, n = 4 electrolaryngeal [EL] voices). Naïve listeners (n = 12) evaluated synthetic, natural, and EL speech for acceptability and intelligibility in a visual sort-and-rate task, as well as phrasal stress discriminability via a classification mechanism. Results: Recorded sEMG signals were processed to translate sEMG muscle activity into lexical content and categorize variations in phrase-level stress, achieving a mean accuracy of 96.3% (SD = 3.10%) and 91.2% (SD = 4.46%), respectively. Synthetic speech was significantly higher in acceptability and intelligibility than EL speech, also leading to greater phrasal stress classification accuracy, whereas natural speech was rated as the most acceptable and intelligible, with the greatest phrasal stress classification accuracy. Conclusion: This proof-of-concept study establishes the feasibility of using subvocal sEMG-based alternative communication not only for lexical recognition but also for prosodic communication in healthy individuals, as well as those living with vocal impairments and residual articulatory function.
Descriptors: Human Body, Speech, Articulation (Speech), Word Recognition, Suprasegmentals, Classification, Audio Equipment, Listening, Auditory Perception, Intelligibility, Adults
American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Institutes of Health (DHHS)
Authoring Institution: N/A
Grant or Contract Numbers: R43DC017097