Regression between EEG and Speech Signals for Spoken Vowels.


Journal

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ISSN: 2694-0604
Titre abrégé: Annu Int Conf IEEE Eng Med Biol Soc
Pays: United States
ID NLM: 101763872

Informations de publication

Date de publication:
Jul 2019
Historique:
entrez: 18 1 2020
pubmed: 18 1 2020
medline: 26 2 2020
Statut: ppublish

Résumé

One of the primary difference of mankind from other species is his ability to communicate verbally. Our brain upon framing a sentence, coordinates with the oro-pharyngeal-laryngeal muscle groups to produce the speech with the help of vocal cord and mouth aperture. However, some individuals due to congenital or illness, may loose their ability to speak in spite of their brain framing speech. Research on speech restoration through brain computer interface (BCI) is still at an early stage. Through this study, we have explored the regression between the chaos parameters of acoustic signal and electroencephalography (EEG) signal for different vowels chosen from International Phonetic Alphabets (IPA). The vowels were categorised into two categories, namely, soft vowels and diphthongs. We have selected the EEG channels based on their higher contribution towards the first principal component. Goodness of fit parameters were evaluated for the regression analysis to explore the most suitable chaos parameter.

Identifiants

pubmed: 31945882
doi: 10.1109/EMBC.2019.8856839
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

221-224

Auteurs

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Classifications MeSH