Spatial Artifact Detection for Multi-channel EMG-based Speech Recognition

Till Heistermann, Matthias Janke, Michael Wand, Tanja Schultz

2014

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 Harvard Style

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

in Bibtex Style

@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},
}


in EndNote Style

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