EARS: ELECTROMYOGRAPHICAL AUTOMATIC RECOGNITION OF SPEECH

Szu-Chen Stan Jou, Tanja Schultz

Abstract

In this paper, we present our research on automatic speech recognition of surface electromyographic signals that are generated by the human articulatory muscles. With parallel recorded audible speech and electromyographic signals, experiments are conducted to show the anticipatory behavior of electromyographic signals with respect to speech signals. Additionally, we demonstrate how to develop phone-based speech recognizers with carefully designed electromyographic feature extraction methods. We show that articulatory feature (AF) classifiers can also benefit from the novel feature, which improve the F-score of the AF classifiers from 0.467 to 0.686. With a stream architecture, the AF classifiers are then integrated into the decoding framework. Overall, the word error rate improves from 86.8% to 29.9% on a 100 word vocabulary recognition task.

References

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Paper Citation


in Harvard Style

Stan Jou S. and Schultz T. (2008). EARS: ELECTROMYOGRAPHICAL AUTOMATIC RECOGNITION OF SPEECH . In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 3-12. DOI: 10.5220/0001067100030012


in Bibtex Style

@conference{biosignals08,
author={Szu-Chen Stan Jou and Tanja Schultz},
title={EARS: ELECTROMYOGRAPHICAL AUTOMATIC RECOGNITION OF SPEECH},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={3-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001067100030012},
isbn={978-989-8111-18-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)
TI - EARS: ELECTROMYOGRAPHICAL AUTOMATIC RECOGNITION OF SPEECH
SN - 978-989-8111-18-0
AU - Stan Jou S.
AU - Schultz T.
PY - 2008
SP - 3
EP - 12
DO - 10.5220/0001067100030012