Towards speaker-adaptive speech recognition based on surface electromyography

BIOSIGNALS 2009 - Proceedings of the 2nd International Conference on Bio-Inspired Systems and Signal Processing

Volumn , Issue , 2009, Pages 155-162

  Wand, Michael ^a   Schultz, Tanja ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

Electromyography; Silent speech; Speech recognition

Indexed keywords

ACOUSTIC MODEL; ADAPTIVE TRAINING; CONTEXT DEPENDENT; ELECTROMYOGRAPHIC SIGNAL; MODEL ADAPTATION; RECOGNITION PERFORMANCE; SILENT SPEECH; SKIN SURFACES; SPEECH INTERFACE; SURFACE ELECTROMYOGRAPHY; TEST DATA; TRAINING DATA;

ACOUSTICS; ELECTROMYOGRAPHY; FEATURE EXTRACTION; SIGNAL PROCESSING;

SPEECH RECOGNITION;

EID: 67650544129     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Chan, A., Englehart, K., Hudgins, B., and Lovely, D. (2002). Hidden Markov Model Classification of My-olectric Signals in Speech. Engineering in Medicine and Biology Magazine, IEEE, 21 (9): 143-146. (Pubitemid 35192262)
2. Dietrich, M. (2008). The Effects of Stress Reactivity on Ex-tralaryngeal Muscle Tension in Vocally Normal Par-ticipants as a Function of Personality. PhD thesis, University of Pittsburgh.
3. Dietrich, M. and Abbott, K. V. (2007). Psychobiological framework of Stress and Voice: A Psychobiological Framework for Studying Psychological Stress and its Relation to Voice Disorders. In: K. Izdebski (Ed.): Emotions in the Human Voice (Vol.11, Clinical Evidence, pp. 159-178). San Diego, Plural Publishing.
4. Finke, M. and Rogina, I. (1997). Wide Context Acoustic Modeling in Read vs. Spontaneous Speech. In Proc. ICASSP, volume 3, pages 1743-1746.
5. Hueber, T., Chollet, G., Denby, B., Dreyfus, G., and Stone, M. (2007). Continuous-Speech Phone Recognition from Ultrasound and Optical Images of the Tongue and Lips. In Proc. Interspeech, pages 658-661.
6. Jorgensen, C. and Binsted, K. (2005). Web Browser Control Using EMG Based Sub Vocal Speech Recognition. In Proceedings of the 38th Hawaii International Conference on System Sciences. (Pubitemid 41544376)
7. Jou, S.-C, Maier-Hein, L., Schultz, T., and Waibel, A. (2006a). Articulatory Feature Classification Using Surface Electromyography. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-2006), Toulouse, France, May 15-19, 2006. (Pubitemid 46499891)
8. Jou, S.-C, Schultz, T., and Waibel, A. (2005). Whispery Speech Recognition Using Adapted Articulatory Fea-tures. In Proc. ICASSP. (Pubitemid 43761326)
9. Jou, S.-C, Schultz, T., Walliczek, M., Kraft, F, and Waibel, A. (2006b). Towards Continuous Speech Recogni-tion using Surface Electromyography. In Proc. Interspeech, Pittsburgh, PA.
10. Kingsbury, N. G. (2000). A Dual-Tree Complex Wavelet Transform with Improved Orthogonality and Symmetry Properties. In Proc. IEEE Conf. on Image Processing, Vancouver.
11. Leggetter, C. J. and Woodland, P. C. (1995). Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models. Computer Speech and Language, 9:171-185.
12. Maier-Hein, L., Metze, F, Schultz, T., and Waibel, A. (2005). Session Independent Non-Audible Speech Recognition Using Surface Electromyography. In Proc. ASRU. (Pubitemid 46091079)
13. Shensa, M. J. (1992). The Discrete Wavelet Transform: Wedding the À Trous and Mallat Algorithms. IEEE Transactions on Signal Processing, 40:2464-2482. (Pubitemid 23555914)
14. Walliczek, M., Kraft, F, Jou, S.-C, Schultz, T, and Waibel, A. (2006). Sub-Word Unit Based Non-Audible Speech Recognition Using Surface Electromyography. In Proc. Interspeech, Pittsburgh, PA.
15. Wand, M., Jou, S.-C. S., and Schultz, T. (2007). Wavelet-based Front-End for Electromyographic Speech Recognition. In Proc. Interspeech.
16. Yu, H. and Waibel, A. (2000). Streamlining the Front End of a Speech Recognizer. In Proc. ICSLP.