Velum Movement Detection based on Surface Electromyography for Speech Interface

João Freitas, António Teixeira, Samuel Silva, Catarina Oliveira, Miguel Sales Dias

2014

Abstract

Conventional speech communication systems do not perform well in the absence of an intelligible acoustic signal. Silent Speech Interfaces enable speech communication to take place with speech-handicapped users and in noisy environments. However, since no acoustic signal is available, information on nasality may be absent, which is an important and relevant characteristic of several languages, particularly European Portuguese. In this paper we propose a non-invasive method – surface Electromyography (EMG) electrodes - positioned in the face and neck regions to explore the existence of useful information about the velum movement. The applied procedure takes advantage of Real-Time Magnetic Resonance Imaging (RT-MRI) data, collected from the same speakers, to interpret and validate EMG data. By ensuring compatible scenario conditions and proper alignment between the EMG and RT-MRI data, we are able to estimate when the velum moves and the probable type of movement under a nasality occurrence. Overall results of this experiment revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered and that it is possible to detect velum movement, particularly by sensors positioned below the ear between the mastoid process and the mandible in the upper neck region.

References

  1. Huang, X., Acero, A., Hon, H., 2001. Spoken Language Processing, Prentice Hall PTR, Upper Saddle River, NJ.
  2. Bell-Berti, F., 1976. An Electromyographic Study of Velopharyngeal Function, Speech Journal of Speech and Hearing Research, Vol.19, pp. 225-240.
  3. Chan, A. D. C., Englehart, K., Hudgins, B. and Lovely, D. F., 2001. Hidden Markov model classification of myoelectric signals in speech. Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 1727-1730.
  4. Denby, B., Schultz, T., Honda, K., Hueber, T., Gilbert, J. M. and Brumberg, J. S, 2009. Silent speech interfaces. Speech Communication, Vol. 52, Issue 4, pp. 270-287.
  5. Flynn, R. and Jones, E., 2008. Combined speech enhancement and auditory modelling for robust distributed speech recognition, Speech Communication, Vol. 50, Issue 10, pp. 797-809.
  6. Freitas, J., Teixeira, A. and Dias, M. S., 2012. Towards a Silent Speech Interface for Portuguese: Surface Electromyography and the nasality challenge, Int. Conf. on Bio-inspired Systems and Signal Processing, Vilamoura, Algarve, Portugal.
  7. Fritzell, B., 1969. The velopharyngeal muscles in speech: an electromyographic and cineradiographic study. Acta Otolaryngolica. Suppl. 50.
  8. Hardcastle, W. J., 1976. Physiology of Speech Production - An Introduction for Speech Scientists, Academic Press.
  9. Herff, C., Janke, M., Wand, M. and Schultz, T., 2011. Impact of Different Feedback Mechanisms in EMGbased Speech Recognition. Interspeech 2011. Florence, Italy.
  10. Hudgins, B., Parker, P. and Scott, R., 1993. A new strategy for multifunction myoelectric control, Biomedical Engineering, IEEE Transactions on, Vol. 40, Issue 1, pp. 82-94.
  11. Jorgensen, C., Lee, D. and Agabon, S., 2003. Sub auditory speech recognition based on EMG signals. In Proc. Internat. Joint Conf. on Neural Networks (IJCNN), pp. 3128-3133.
  12. Jou, S., Schultz, T. and Waibel, A., 2007. Continuous Electromyographic Speech Recognition with a MultiStream Decoding Architecture. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2007, Honolulu, Hawaii, US.
  13. Kuehn D. P., Folkins J.W. and Cutting C. B., 1982. Relationships between muscle activity and velar position, Cleft Palate Journal, Vol. 19, Issue 1, pp. 25- 35.
  14. Kuehn D. P., Folkins J.W. and Linville R. N., 1988. An Electromyographic Study of the Musculus Uvulae, Cleft Palate Journal, Vol. 25, Issue 4, pp. 348-355.
  15. Lacerda, A. and Head, B. F., 1996. Análise de sons nasais e sons nasalizados do Português. Revista do Laboratório de Fonética Experimental (de Coimbra), No.6, pp. 5-70.
  16. Lubker, J. F., 1968. An electromyographiccinefluorographic investigation of velar function during normal speech production, Cleft Palate Journal, Vol. 5, Issue 1, pp. 17.
  17. Martins, P. Carbone, I. Pinto, A. Silva, A. and Teixeira, A., 2008. European Portuguese MRI based speech production studies. Speech Communication. NL: Elsevier, Vol. 50, No.11/12, ISSN 0167-6393, pp. 925-952.
  18. McGill, S., Juker, D. and Kropf, P., 1996. Appropriately placed surface EMG electrodes reflect deep muscle activity (psoas, quadratus lumborum, abdominal wall) in the lumbar spine, Journal of Biomechanics, Vol. 29, Issue 11, pp. 1503-7.
  19. Plux Wireless Biosignals, Portugal, 2013. Available from: http://www.plux.info/. (accessed on December 20. 2013).
  20. Rossato, S. Teixeira, A. and Ferreira, L., 2006. Les Nasales du Portugais et du Français: une étude comparative sur les données EMMA. In XXVI Journées d'Études de la Parole. Dinard, France.
  21. Schultz, T. and Wand. M., 2010. Modeling coarticulation in large vocabulary EMG-based speech recognition. Speech Communication, Vol. 52, Issue 4, pp. 341-353.
  22. Seikel, J. A., King, D. W., Drumright, D. G., 2010. Anatomy and Physiology for Speech, Language, and Hearing, Delmar Learning, 4rd Ed.
  23. Silva, S., Martins, P., Oliveira, C., Silva, A. and Teixeira, A., 2012. Segmentation and Analysis of the Oral and Nasal Cavities from MR Time Sequences, Image Analysis and Recognition. Proceedings of ICIAR 2012, LNCS, Springer.
  24. Stark, A. and Paliwal, K., 2011. MMSE estimation of logfilterbank energies for robust speech recognition, Speech Communication, Vol. 53, Issue 3, pp. 403-416.
  25. Teixeira, A., Moutinho, L. C. and Coimbra, R. L., 2003. Production, acoustic and perceptual studies on European Portuguese nasal vowels height. In Internat. Congress Phonetic Sciences (ICPhS), pp. 3033-3036.
  26. Teixeira, A., Martins, P., Oliveira, C., Ferreira, C., Silva, A. And Shosted, R., 2012. Real-time MRI for Portuguese: database, methods and applications, Proceedings of PROPOR 2012, LNCS vol. 7243. pp. 306-317.
  27. Teixeira, J. S., 2000. Síntese Articulatória das Vogais Nasais do Português Europeu [Articulatory Synthesis of Nasal Vowels for European Portuguese]. PhD Thesis, Universidade de Aveiro.
  28. Trigo, R. L., 1993. The inherent structure of nasal segments, In Nasals, Nasalization, and the Velum, Phonetics and Phonology, M. K. Huffman e R. A. Krakow (eds.), Academic Press Inc., Vol. 5, pp. 369- 400.
  29. Wand, M. and Schultz, T., 2011a. Investigations on Speaking Mode Discrepancies in EMG-based Speech Recognition, Interspeech 2011, Florence, Italy.
  30. Wand, M. and Schultz, T., 2011b. Analysis of Phone Confusion in EMG-based Speech Recognition. IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2011, Prague, Czech Republic.
  31. Wand, M. and Schultz, T., 2011c. Session-Independent EMG-based Speech Recognition. International Conference on Bio-inspired Systems and Signal Processing 2011, Biosignals 2011, Rome, Italy.
  32. Wand, M., Schulte, C., Janke, M. and Schultz, T., 2013. Array-based Electromyographic Silent Speech Interface. In 6th International Conference on Bioinspired Systems and Signal Processing, Biosignals 2013, Barcelona, Spain.
  33. Yang, C.; Brown, G., Lu, L., Yamagishi, J. and King, S., 2012. Noise-robust whispered speech recognition using a non-audible-murmur microphone with VTS compensation. Chinese Spoken Language Processing (ISCSLP), 2012 8th International Symposium on, pp. 220-223.
Download


Paper Citation


in Harvard Style

Freitas J., Teixeira A., Silva S., Oliveira C. and Dias M. (2014). Velum Movement Detection based on Surface Electromyography for Speech Interface . 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 13-20. DOI: 10.5220/0004741100130020


in Bibtex Style

@conference{biosignals14,
author={João Freitas and António Teixeira and Samuel Silva and Catarina Oliveira and Miguel Sales Dias},
title={Velum Movement Detection based on Surface Electromyography for Speech Interface},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={13-20},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004741100130020},
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 - Velum Movement Detection based on Surface Electromyography for Speech Interface
SN - 978-989-758-011-6
AU - Freitas J.
AU - Teixeira A.
AU - Silva S.
AU - Oliveira C.
AU - Dias M.
PY - 2014
SP - 13
EP - 20
DO - 10.5220/0004741100130020