Enhanced speech recognition using an articulatory production model trained on X-ray data

Computer Speech and Language

Volumn 15, Issue 3, 2001, Pages 195-215

  Blackburn, C Simon ^a   Young, Steve ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; DYNAMIC PROGRAMMING; MARKOV PROCESSES; NEURAL NETWORKS; PROBABILITY DISTRIBUTIONS; SPEECH ANALYSIS;

ARTICULATORY PRODUCTION MODEL; HIDDEN MARKOV MODEL;

SPEECH RECOGNITION;

EID: 0035412933     PISSN: 08852308     EISSN: None     Source Type: Journal    
DOI: 10.1006/csla.2001.0165     Document Type: Article

References (45)

1. Akagi, M. & Tohkura, Y. (1990). Spectrum target prediction model and its application to speech recognition. Computer Speech and Language, 4, 325-344.
2. Atal, B. S., Chang, J. J., Mathews, M. V. & Tukey, J. W. (1978). Inversion of articulatory-to-acoustic transformation in the vocal tract by a computer-sorting technique. Journal of the Acoustical Society of America, 63, 1535-1555.
3. Austin, S., Zavaliagkos, G., Makhoul, J. & Schwartz, R. (1992). Improving state-of-the-art continuous speech recognition systems using the N-best paradigm with neural networks. Proceedings of the DARPA Workshop on Speech and Natural Language, Morgan Kaufmann, pp. 180-184.
4. Bakis, R. (1991). Coarticulation modelling with continuous-state HMMs. In IEEE Speech Recognition Workshop, Arden House, IEEE.
5. Benguerel, A. P. & Cowan, H. A. (1974). Coarticulation of upper lip protrusion in French. Phonetica, 30, 41-55.
6. Bishop, C. M. (1995). Neural Networks for Pattern Recognition, Oxford University Press.
7. Blackburn, C. S. (1996). Articulatory methods for speech production and recognition. PhD Thesis, University of Cambridge.
8. Blackburn, C. S. & Young, S. J. (1995). Learning new articulator trajectories for a speech production model using artificial neural networks. IEEE International Conference on Neural Networks, 4, 2046-2051.
9. Blackburn, C. S. & Young, S. J. (1996). Pseudo-articulatory speech synthesis for recognition using automatic feature extraction from X-ray data. Proceedings of the International Conference on Speech and Language Processing, volume 2, pp. 969-972.
10. Blackburn, C. S. & Young, S. J. (2000). A self-learning predictive model of articulator movements during speech production. Journal of the Acoustical Society of America, 107, 1659-1670.
11. Blomberg, M. (1994). A common phone model representation for speech recognition and synthesis. Proceedings of the International Conference on Speech and Language Processing, volume 4, pp. 1875-1878.
12. Deng, L., Ramsay, G. & Sund, D. (1996). Production models as a structural basis for automatic speech recognition. In 1st ESCA Tutorial and Research Workshop on Speech Production Modeling, pp. 69-80.
13. Deng, L. & Sund, D. X. (1994). A statistical approach to automatic speech recognition using the atomic speech units constructed from overlapping articulatory features. Journal of the Acoustical Society of America, 95, 2702-2719.
14. Hirayama, M., Vatikiotis-Bateson, E., Kawato, M. & Jordan, M. I. (1992). Forward dynamics modeling of speech motor control using physiological data. In Advances in Neural Information Processing Systems 4 (J. E. Moody, S. J. Hanson and R. P. Lippmann, eds), pp. 191-198. Morgan Kaufman, USA.
15. Holmes, W. J. & Russell, M. J. (1999). Probabilistic Trajectory segmental HMMs. Computer Speech and Language, 13, 3-37.
16. Jervis, T. T. (1993). Connectionist adaptive control. PhD Thesis, University of Cambridge.
17. Keating, P. A. (1988). Underspecification in phonetics. In Coarticulation, pp. 30-50. UCLA phonetics laboratory.
18. Keating, P. A. (1990). The window model of coarticulation: articulatory evidence. In Papers in Laboratory Phonology I. (J. Kingston and M. E. Beckman, eds), chapter 26, pp. 451-470. Cambridge University Press. Cambridge.
19. Kuwabara, H. (1985). An approach to normalisation of coarticulation effects for vowels in connected speech. Journal of the Acoustical Society of America, 77, 686-694.
20. Laboissière, R., Ostry, D. J. & Perrier, P. (1995). A model of human jaw and hyoid motion and its implications for speech production. International Congress of Phonetic Sciences, 2, 60-67.
21. Lee, K.-F. (1989). Automatic Speech Recognition. Kluwer Academic Publishers.
22. Levinson, S. E. & Schmidt, C. E. (1983). Adaptive computation of articulatory parameters from the speech signal. Journal of the Acoustical Society of America, 74, 1145-1154.
23. Lindblom, B. (1983), Economy of speech gestures. In The Production of Speech. (P.F. MacNeilage, ed.), chapter 10, pp. 217-246. Springer-Verlag, New York.
24. Lubker, J. F. (1981). Temporal aspects of speech production: Anticipatory labial coarticulation. Phonetica, 38, 51-65.
25. Marcus, J. N. & Zue, V. W. (1991). A variable duration acoustic segment HMM for hard-to-recognize words and phrases. Proceedings of the International Conference on Acoustics, Speech and Signal Processing, Toronto, volume 1, pp. 281-284.
26. Massey, F. J. Jr. (1951). The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 46, 68-78.
27. Meyer, P., Wilhelms, R. & Strube, H. W. (1989). A quasiarticulatory speech synthesizer for German language running in real time. Journal of the Acoustical Society of America, 86, 523-539.
28. Mood, A. M., Graybill, F. A. & Boes, D. C. (1974). Introduction to the Theory of Statistics, 3rd edition. McGraw-Hill.
29. Nelson, W. L. (1983). Physical principles for economies of skilled movements. Biological Cybernetics, 46, 135-147.
30. Ostendorf, M., Digalakis, V. & Kimball, O. (1996). From HMMs to segment models: a unified view of stochastic modeling for speech recognition. IEEE Transactions on Speech and Audio Processing, 4, 360-378.
31. Ostendorf, M., Kannan, A., Austin, S., Kimball, O., Schwartz, R. & Rohlicek, J. R. (1991). Integration of diverse recognition methodologies through reevaluation of N-best sentence hypotheses. Proceedings of the DARPA Workshop on Speech and Natural Language, Morgan Kaufmann, pp. 83-87.
32. Paliwal, K. K. & Rao, P. V. S. (1982). Synthesis-based recognition of continuous speech. Journal of the Acoustical Society of America, 71, 1016-1024.
33. Ramsay, G. & Deng, L. (1994). A stochastic framework for articulatory speech recognition. Journal of the Acoustical Society of America, 95 (5 Part 2), 2873. Apbstract 2pSP19.
34. Randolph, M. A. (1994). Speech analysis based on a model of articulatory behaviour. Journal of the Acoustical Society of America, 95(5 Pt. 2), 2818.
35. Riedmiller, M. & Braun, H. (1993). A direct adaptive method for faster backpropagation learning: the RPROP algorithm. IEEE International Conference on Neural Networks.
36. Robinson, A. J. (1994) An application of recurrent nets to phone probability estimation. IEEE Transactions on Neural Networks, 5.
37. Roweis, S. (2000). Constrained hidden Markov models. Proc Neural Information Processing Systems, 13, 782-788.
38. Rubin, P., Baer, T. & Mermelstein, P. (1981). An articulatory synthesizer for perceptual research. Journal of the Acoustical Society of America, 70, 321-328.
39. Schwatrz, R., Ausin, S., Kubala, F., Makhoul, J., Nguyen, L., Placeway, P. & Zavaliagkos, G. (1992). New uses for the N-best sentence hypotheses within the BYBLOS speech recognition system. Proceedings of the International Conference on Acoustics, Speech and Signal Processing, volume 1, pp. 1-4.
40. Sondhi, M. M. & Schroeter, J. (1987). A hybrid time-frequency domain articulatory speech synthesizer. IEEE Transactions on Acoustics, Speech and Signal Processing, 35, 955-967.
41. Stevens, K. N., Bickley, C. A. & Williams, D. R. (1994). Control of a Klatt synthesizer by articulatory parameters. Proceedings of the International Conference on Speech and Language Processing, volume 1, pp. 183-186.
42. Westbury, J. R. (1994). X-Ray microbeam speech production database user's handbook. University of Wisconsin. Personal communication.
43. Wilhelms-Tricarico, R. (1995). Physiological modeling of speech production: methods for modeling soft-tissue articulators. Journal of the Acoustical Society of America, 97(5 Part 1). 3085-3098.
44. Young, S. J., Kershaw, D. J., Odell, J. J., Ollason, D., Valtchev, V. & Woodland, P. C. (1999). Speech Input/Output. In The HTK Book Version 2.2. Section 5.4, Entropic Ltd, Cambridge , England (also available via http://htk.eng.cam.ac.uk).
45. Young, S. J., Odell, J. J. & Woodland, P. C. (1994). Tree-based state tying for high accuracy acoustic modelling. In ARPA Workshop on Human Language Technology, Morgan Kaufmann, pp. 307-312.