Publication in conference proceedings
Velum movement detection based on surface electromyography for speech interface
João Freitas (Freitas, J.); António Teixeira (Teixeira, A.); Miguel Sales Dias (Dias, J.); Catarina Oliveira (Oliveira, C.);
Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - BIOSIGNALS
Year (definitive publication)
2014
Language
English
Country
Portugal
More Information
Web of Science®

This publication is not indexed in Web of Science®

Scopus

Times Cited: 9

(Last checked: 2026-04-12 15:44)

View record in Scopus

Google Scholar

Times Cited: 16

(Last checked: 2026-02-21 06:58)

View record in Google Scholar

This publication is not indexed in Overton

Abstract
Conventional speech communication systems do not perform well in the absence of an intelligible acoustic signal. Silent Speech Interfaces enable speech communication to take place with speech-handicapped users and in noisy environments. However, since no acoustic signal is available, information on nasality may be absent, which is an important and relevant characteristic of several languages, particularly European Portuguese. In this paper we propose a non-invasive method - surface Electromyography (EMG) electrodes - positioned in the face and neck regions to explore the existence of useful information about the velum movement. The applied procedure takes advantage of Real-Time Magnetic Resonance Imaging (RT-MRI) data, collected from the same speakers, to interpret and validate EMG data. By ensuring compatible scenario conditions and proper alignment between the EMG and RT-MRI data, we are able to estimate when the velum moves and the probable type of movement under a nasality occurrence. Overall results of this experiment revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered and that it is possible to detect velum movement, particularly by sensors positioned below the ear between the mastoid process and the mandible in the upper neck region.
Acknowledgements
--
Keywords
Nasal Vowels Detection,Surface Electromyography,Silent Speech Interfaces
  • Computer and Information Sciences - Natural Sciences