Array-based Electromyographic Silent Speech Interface

Michael Wand, Christopher Schulte, Matthias Janke, Tanja Schultz


An electromygraphic (EMG) Silent Speech Interface is a system which recognizes speech by capturing the electric potentials of the human articulatory muscles, thus enabling the user to communicate silently. This study is concerned with introducing an EMG recording system based on multi-channel electrode arrays. We first present our new system and introduce a method to deal with undertraining effects which emerge due to the high dimensionality of our EMG features. Second, we show that Independent Component Analysis improves the classification accuracy of the EMG array-based recognizer by up to 22.9% relative, which is a first example of an EMG signal processing method which is specifically enabled by our new array-based system. We evaluate our system on recordings of audible speech; achieving an optimal average word error rate of 10.9% with a training set of less than 10 minutes on a vocabulary of 108 words.


  1. Belhumeur, P. N., Hespanha, J. P., and Kriegman, D. J. (1997). Eigenfaces vs Fisherface: Recognition using Class-specific Linear Projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19:711 - 720.
  2. Bell, A. J. and Sejnowski, T. I. (1995). An InformationMaximization Approach to Blind Separation and Blind Deconvolution. Neural Computation, 7:1129 - 1159.
  3. Denby, B., Schultz, T., Honda, K., Hueber, T., and Gilbert, J. (2010). Silent Speech Interfaces. Speech Communication, 52(4):270 - 287.
  4. Freitas, J., Teixeira, A., and Dias, M. S. (2012). Towards a Silent Speech Interface for Portuguese. In Proc. Biosignals.
  5. Hyvrinen, A. and Oja, E. (2000). Independent Component Analysis: Algorithms and Applications. Neural Networks, 13:411 - 430.
  6. Jorgensen, C. and Dusan, S. (2010). Speech Interfaces based upon Surface Electromyography. Speech Communication, 52:354 - 366.
  7. Jou, S.-C., Schultz, T., Walliczek, M., Kraft, F., and Waibel, A. (2006). Towards Continuous Speech Recognition using Surface Electromyography. In Proc. Interspeech, pages 573 - 576, Pittsburgh, PA.
  8. Jung, T., Makeig, S., Humphries, C., Lee, T., Mckeown, M., Iragui, V., and Sejnowski, T. (2000). Removing Electroencephalographic Artifacts by Blind Source Separation. Psychophysiology, 37:163 - 178.
  9. Lopez-Larraz, E., Mozos, O. M., Antelis, J. M., and Minguez, J. (2010). Syllable-Based Speech Recognition Using EMG. In Proc. IEEE EMBS.
  10. Maier-Hein, L., Metze, F., Schultz, T., and Waibel, A. (2005). Session Independent Non-Audible Speech Recognition Using Surface Electromyography. In IEEE Workshop on Automatic Speech Recognition and Understanding, pages 331 - 336, San Juan, Puerto Rico.
  11. Makeig, S. et al. (2000). EEGLAB: ICA Toolbox for Psychophysiological Research. WWW Site, Swartz Center for Computational Neuroscience, Institute of Neural Computation, University of San Diego California:
  12. Qiao, Z., Zhou, L., and Huang, J. Z. (2009). Sparse Linear Discriminant Analysis with Applications to High Dimensional Low Sample Size Data. International Journal of Applied Mathematics, 39:48 - 60.
  13. Schultz, T. and Wand, M. (2010). Modeling Coarticulation in Large Vocabulary EMG-based Speech Recognition. Speech Communication, 52(4):341 - 353.
  14. Ueda, N., Nakano, R., Ghahramani, Z., and Hinton, G. E. (2000). Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. Journal of VLSI Signal Processing, 26:133 - 140.
  15. Wand, M. and Schultz, T. (2010). Speaker-Adaptive Speech Recognition Based on Surface Electromyography. In Fred, A., Filipe, J., and Gamboa, H., editors, Biomedical Engineering Systems and Technologies, volume 52 of Communications in Computer and Information Science, pages 271-285. Springer Berlin Heidelberg.
  16. Winter, B. B. and Webster, J. G. (1983). Driven-right-leg Circuit Design. IEEE Trans. Biomed. Eng., BME30:62 - 66.

Paper Citation

in Harvard Style

Wand M., Schulte C., Janke M. and Schultz T. (2013). Array-based Electromyographic Silent Speech Interface . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 89-96. DOI: 10.5220/0004252400890096

in Bibtex Style

author={Michael Wand and Christopher Schulte and Matthias Janke and Tanja Schultz},
title={Array-based Electromyographic Silent Speech Interface},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - Array-based Electromyographic Silent Speech Interface
SN - 978-989-8565-36-5
AU - Wand M.
AU - Schulte C.
AU - Janke M.
AU - Schultz T.
PY - 2013
SP - 89
EP - 96
DO - 10.5220/0004252400890096