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Authors: Till Heistermann ; Matthias Janke ; Michael Wand and Tanja Schultz

Affiliation: Karlsruhe Institute of Technology, Germany

ISBN: 978-989-758-011-6

Keyword(s): Silent Speech Interfaces, EMG, Artifact Removal, ICA, Speech Recognition, Array Processing.

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

Abstract: We introduce a spatial artifact detection method for a surface electromyography (EMG) based speech recognition system. The EMG signals are recorded using grid-shaped electrode arrays affixed to the speakers face. Continuous speech recognition is performed on the basis of these signals. As the EMG data are highdimensional, Independent Component Analysis (ICA) can be applied to separate artifact components from the content-bearing signal. The proposed artifact detection method classifies the ICA components by their spatial shape, which is analyzed using the spectra of the spatial patterns of the independent components. Components identified as artifacts can then be removed. Our artifact detection method reduces the word error rates (WER) of the recognizer significantly. We observe a slight advantage in terms of WER over the temporal signal based artifact detection method by (Wand et al., 2013a).

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Paper citation in several formats:
Heistermann, T.; Janke, M.; Wand, M. and Schultz, T. (2014). Spatial Artifact Detection for Multi-channel EMG-based Speech Recognition.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 189-196. DOI: 10.5220/0004793901890196

@conference{biosignals14,
author={Till Heistermann. and Matthias Janke. and Michael Wand. and Tanja Schultz.},
title={Spatial Artifact Detection for Multi-channel EMG-based Speech Recognition},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={189-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004793901890196},
isbn={978-989-758-011-6},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - Spatial Artifact Detection for Multi-channel EMG-based Speech Recognition
SN - 978-989-758-011-6
AU - Heistermann, T.
AU - Janke, M.
AU - Wand, M.
AU - Schultz, T.
PY - 2014
SP - 189
EP - 196
DO - 10.5220/0004793901890196

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