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Authors: Michael Wand ; Matthias Janke and Tanja Schultz

Affiliation: Karlsruhe Institute of Technology, Germany

Keyword(s): EMG, EMG-based speech recognition, Silent speech interfaces, Phonetic decision tree.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Devices ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Speech Recognition ; Wearable Sensors and Systems

Abstract: This study is concerned with the impact of speaking mode variabilities on speech recognition by surface electromyography (EMG). In EMG-based speech recognition, we capture the electric potentials of the human articulatory muscles by surface electrodes, so that the resulting signal can be used for speech processing. This enables the user to communicate silently, without uttering any sound. Previous studies have shown that the processing of silent speech creates a new challenge, namely that EMG signals of audible and silent speech are quite distinct. In this study we consider EMG signals of three speaking modes: audibly spoken speech, whispered speech, and silently mouthed speech. We present an approach to quantify the differences between these speaking modes by means of phonetic decision trees and show that this measure correlates highly with differences in the performance of a recognizer on the different speaking modes. We furthermore reinvestigate the spectral mapping algorithm, whi ch reduces the discrepancy between different speaking modes, and give an evaluation of its effectiveness. (More)

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Paper citation in several formats:
Wand, M.; Janke, M. and Schultz, T. (2012). DECISION-TREE BASED ANALYSIS OF SPEAKING MODE DISCREPANCIES IN EMG-BASED SPEECH RECOGNITION. In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2012) - BIOSIGNALS; ISBN 978-989-8425-89-8; ISSN 2184-4305, SciTePress, pages 101-109. DOI: 10.5220/0003787201010109

@conference{biosignals12,
author={Michael Wand. and Matthias Janke. and Tanja Schultz.},
title={DECISION-TREE BASED ANALYSIS OF SPEAKING MODE DISCREPANCIES IN EMG-BASED SPEECH RECOGNITION},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2012) - BIOSIGNALS},
year={2012},
pages={101-109},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003787201010109},
isbn={978-989-8425-89-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2012) - BIOSIGNALS
TI - DECISION-TREE BASED ANALYSIS OF SPEAKING MODE DISCREPANCIES IN EMG-BASED SPEECH RECOGNITION
SN - 978-989-8425-89-8
IS - 2184-4305
AU - Wand, M.
AU - Janke, M.
AU - Schultz, T.
PY - 2012
SP - 101
EP - 109
DO - 10.5220/0003787201010109
PB - SciTePress