ISCA Archive IberSPEECH 2022
ISCA Archive IberSPEECH 2022

Phone classification using electromyographic signals 

Eder Del Blanco, Inge Salomons, Eva Navas, Inma Hernáez

Silent speech interfaces aim at generating speech from biosignals obtained from the human speech production system. In order to provide resources for the development of these interfaces, language-specific databases are required. Several silent speech electromyography (EMG) databases for English exist. However, a database for the Spanish language had yet to be developed. The aim of this research is to validate the experimental design of the first silent speech EMG database for Spanish, namely the new ReSSInt-EMG database. The EMG signals in this database are obtained using eight surface EMG bipolar electrode pairs located in the face and neck and are recorded in parallel with either audible or silent speech. Phone classification experiments are performed, using a set of time-domain features typically used in related works. As a validation reference, the EMG-UKA Trial Corpus is used, which is the most commonly used silent speech EMG database for English. The results show an average test accuracy of 40.85% for ReSSInt- EMG, suggesting that the data acquisition procedure for the new database is valid.


doi: 10.21437/IberSPEECH.2022-7

Cite as: Blanco, E.D., Salomons, I., Navas, E., Hernáez, I. (2022) Phone classification using electromyographic signals . Proc. IberSPEECH 2022, 31-35, doi: 10.21437/IberSPEECH.2022-7

@inproceedings{blanco22_iberspeech,
  author={Eder Del Blanco and Inge Salomons and Eva Navas and Inma Hernáez},
  title={{Phone classification using electromyographic signals }},
  year=2022,
  booktitle={Proc. IberSPEECH 2022},
  pages={31--35},
  doi={10.21437/IberSPEECH.2022-7}
}