Multiexpert automatic speech recognition using acoustic and myoelectric signals

IEEE Transactions on Biomedical Engineering

Volumn 53, Issue 4, 2006, Pages 676-685

  Chan, Adrian D C ^a,b,e,f   Englehart, Kevin B ^a,c,e,f,g,h   Hudgins, Bernard ^a,c,d,i   Lovely, Dennis F ^a,d,f,j  

^a IEEE   (Canada)

^b CARLETON UNIVERSITY   (Canada)

^c UNIVERSITY OF NEW BRUNSWICK   (Canada)

^d UNIVERSITY OF NEW BRUNSWICK   (Canada)

^e IEEE

^f Canadian Medical and Biological Engineering Society   (Canada)

^g UNB ^*  (Canada)

^h UNB

ⁱ Institute of Biomedical Engineering   (Brazil)

^j Natural Science and Engineering Research Council (NSERC)   (Canada)

more..

Author keywords

Classification; Electromyography; Multiexpert system; Myoelectric signals; Speech recognition

Indexed keywords

CLASSIFICATION; MULTIEXPERT SYSTEM; MYOELECTRIC SIGNALS; PLAUSIBILITY METHOD;

ACOUSTIC NOISE; ELECTROMYOGRAPHY; PERFORMANCE; SIGNAL PROCESSING;

SPEECH RECOGNITION;

ACOUSTICS; ARTICLE; AUTOMATION; CLASSIFICATION; EVIDENCE BASED PRACTICE; EXPERT SYSTEM; FACE MUSCLE; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; LINGUISTICS; MALE; MATHEMATICAL ANALYSIS; MYOELECTRICITY; NOISE; NORMAL HUMAN; SCORING SYSTEM; SPEECH DISCRIMINATION;

ALGORITHMS; ELECTROMYOGRAPHY; EXPERT SYSTEMS; FACIAL MUSCLES; FEASIBILITY STUDIES; HUMANS; MALE; MUSCLE CONTRACTION; PATTERN RECOGNITION, AUTOMATED; SOUND SPECTROGRAPHY; SPEECH INTELLIGIBILITY; SPEECH PERCEPTION; SPEECH PRODUCTION MEASUREMENT; SPEECH RECOGNITION SOFTWARE;

EID: 33645295504     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2006.870224     Document Type: Article

References (31)

1. Research and Technology Organization - North Atlantic Treaty Organization, "Alternative Control Technologies,", RTO Technical Report 7, 1998.
2. L. Deng, J. Droppo, and A. Acero, "Recursive estimation of nonstationary noise using iterative stochastic approximation for robust speech recognition," IEEE Trans. Speech Audio Process., vol. 11, no. 6, pp. 568-580, Nov. 2003.
3. Y. Zhao, "Frequency-domain maximum likelihood estimation for automatic speech recognition in additive and convolutive noises," IEEE Trans. Speech Audio Process., vol. 8, no. 3, pp. 255-266, May 2000.
4. B. Duc, E. S. Bigun, J. Bigun, G. Maitre, and S. Fischer, "Fusion of audio and video information for multi-modal person authentication," Pattern Recognit. Lett., vol. 18, pp. 835-843, 1997.
5. A. D. C. Chan, K. Englehart, B. Hudgins, and D. F. Lovely, "Myoelectric signals to augment speech recognition," Med. Biol. Eng. Comput., vol. 39, no. 4, pp. 500-504, 2001.
6. K. Englehart, B. Hudgins, P. A. Parker, and M. Stevenson, "Classification of the myoelectric signal using time-frequency based representations," Med. Eng. Phys., vol. 21, pp. 431-438, 1999.
7. M. S. Morse and E. M. O'Brien, "Research summary of a scheme to ascertain the availability of speech information in the myoelectric signals of neck and head muscles using surface electrodes," Comput. Biol. Med., vol. 16, pp. 399-410, 1986.
8. N. Sugie and K. Tsunoda, "A speech prosthesis employing a speech synthesizer - vowel discrimination from perioral muscle activities and vowel production," IEEE Trans. Biomed. Eng., vol. BME-32, pp. 485-490, 1985.
9. S. H. Day, "Recognition of speech utilizing the myoelectric signals of neck muscles - An advanced study in the time domain," M.Sc. thesis, Auburn Univ., Auburn, AL, 1990.
10. D. W. Long, "Speech recognition from myoelectric signals - Frequency spectrum shaping effects on speech recognition," M.Sc. thesis, Auburn Univ., Auburn, AL, 1990.
11. A. D. C. Chan, K. Englehart, B. Hudgins, and D. F. Lovely, "Hidden Markov model classification of myoelectric signals in speech," IEEE EMBS Magazine, vol. 21, no. 4, pp. 143-146, 2002.
12. M. Hiroyuki, A. Hiraiwa, and T. Sugimura, "Unvoice speech recognition using EMG - mime speech recognition," in Proc. Conf. Computer Human Interaction, Ft. Lauderdale, FL, 2003, pp. 794-795.
13. C. Jorgensen, D. D. Lee, and S. Agabon, "Sub auditory speech recognition based on EMG signals," in Proc. Int. Conf. Neural Network, Portland, OR, 2003, pp. 3128-3133.
14. J. J. O'Neill, "Contributions of the visual components of oral symbols to speech comprehension," J. Speech Hear. Disorders, vol. 19, pp. 429-439, 1954.
15. W. H. Sumby and I. Pollack, "Visual contribution to speech intelligibility in noise," J. Acoust. Soc. Amer., vol. 26, no. 20, pp. 212-215, 1954.
16. R. Brunelli and D. Falavigna, "Person identification using multiple cues," IEEE Trans. Pattern Anal. Mach. Intell., vol. 17, no. 10, pp. 955-966, Oct. 1995.
17. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their application to handwriting recognition," IEEE Trans. Syst., Man, Cybern., vol. 22, no. 3, pp. 418-435, May-Jun. 1992.
18. C. Black, The Theory of Committees and Elections, 2nd ed. London, U.K.: Cambridge Univ. Press, 1963.
19. B. Achermann and H. Bunke, "Combination of face classifiers for person identification," in Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria, 1996, pp. 416-420.
20. K. Yu, X. Jiang, and H. Bunke, "Lip reading: A classifier combination approach," Pattern Recognit. Lett., vol. 18, pp. 1421-1426, 1997.
21. A. P. Dempster, "Upper and lower probabilities induced by a multivalued mapping," A. Math. Staist., vol. 38, pp. 325-339, 1967.
22. G. Shafer, A Mathematical Theory of Evidence. Princeton, NJ: Princeton Univ. Press, 1976.
23. E. Mandler and J. Schurmann, "Combining the classification results of independent classifiers based on the Dempster-Shafer theory of evidence," in Proc. Pattern Recog. in Practice (Pattern Recognition and Artificial Intelligence - Toward an Integration), E. S. Gelsema and L. N. Kanal, Eds., Amsterdam, Netherlands, 1988, pp. 381-393.
24. G. Rogova, "Combining the results of several neural network classifiers," Neural Netw., vol. 7, pp. 777-781, 1994.
25. A. Al-Ani and M. Deiche, "A Dempster-Shafer theory of evidence approach for combining trained neural networks," in IEEE Int. Symp. Circuits Systems, vol. 2, Sydney, Australia, 2001, pp. 703-706.
26. D. F. Lovely, "Low noise electrode amplifier for use in evoked potential studies," in Proc. CMBEC19, Ottawa, ON, Canada, 1993, pp. 236-237.
27. J. C. Junque, "The Lombard reflex and its role on human listeners and automatic speech recognizers," J. Acoust. Soc. Am., vol. 93, no. 1, pp. 510-524, 1993.
28. L. Rabiner and B. H. Juang, Fundamentals of Speech Recognition. Englewood Cliffs, NJ: Prentice-Hall, 1993.
29. H. S. Park and S. W. Lee, "Off-line recognition of large-set handwritten characters with multiple hidden Markov models," Pattern Recognit., vol. 29, no. 2, pp. 231-244, 1996.
30. A. F. R. Rahman and M. C. Fairhurst, "A new hybrid approach in combining multiple experts to recognize handwritten numerals," Pattern Recognit. Lett., vol. 18, pp. 781-790, 1997.
31. F. Voorbraak, "On the justification of Dempster's rule of combination," Artif. Intell., vol. 48, pp. 171-197, 1991.