Segmental modeling using a continuous mixture of nonparametric models

IEEE Transactions on Speech and Audio Processing

Volumn 7, Issue 3, 1999, Pages 262-271

  Goldberger, Jacob ^a   Burshtein, David ^b   Franco, Horacio ^c  

^a TEL AVIV UNIVERSITY   (Israel)

^b SRI INTERNATIONAL   (United States)

^c IEEE

Author keywords

[No Author keywords available]

Indexed keywords

MARKOV PROCESSES; MATHEMATICAL MODELS; SPEECH ANALYSIS; SPEECH PROCESSING; VECTORS;

HIDDEN MARKOV MODELS; MIXTURE MODELS; SEGMENTAL MODELING;

SPEECH RECOGNITION;

EID: 0032636332     PISSN: 10636676     EISSN: None     Source Type: Journal    
DOI: 10.1109/89.759032     Document Type: Article

References (26)

1. L. Deng, M. Aksmanovic, D. Sun, and J. Wu, "Speech recognition using hidden Markov models with polynomial regression functions as nonstationary states," IEEE Trans. Speech, Audio Processing, vol. 2, pp. 507-520, 1994.
2. L. Deng and C. Rathinavelu, "A Markov model containing stateconditioned second order nonstationary: Application to speech recognition," Comput. Speech Lang., vol. 9, pp. 63-86, 1995.
3. G. Doddington, "CSR corpus development," in Proc. AKPA Workshop on Spoken Language Technology, Feb. 1992.
4. V. V. Digalakis, "Segment-based stochastic models of spectral dynamics for continuous speech recognition," Ph.D. dissertation, Boston Univ., Boston, MA, 1992.
5. V. V. Digalakis, P. Monaco, and H. Murveit, "Genones: Generalized mixture tying in continuous hidden Markov model-based speech recognizers," IEEE Trans. Speech, Audio Processing, vol. 4, pp. 281-289, 1996.
6. M. Gales and S. J. Young, "The theory of segmental hidden Markov models," Tech. Rep. CUED/F-INFENG/TR 133, Cambridge, U.K., 1993.
7. "Segmental hidden Markov models," in Proc. Eurospeech, 1995, pp. 1579-1582.
8. O. Ghitza and M. Sondhi, "Hidden Markov models with templates as nonstationary states: An application to speech recognition," Comput. Speech Lang., vol. 7, pp. 101-119, 1993.
9. H. Gish and K. Ng, "A segmental speech model with applications to nonstationary states: An application to speech recognition," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1993, pp. 447-450.
10. J. Goldberger and D. Burshtein, "Scaled random trajectory segment models," Comput. Speech Lang., vol. 12, pp. 51-73, 1998.
11. W. D. Goldenthal, "Statistical trajectory models for phonetic recognition," Ph.D. dissertation, Mass. Inst. Technol., Cambridge, 1994.
12. W. Holmes and M. Russell, "Experimental evaluation of segmental HMM's," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1995, pp. 536-539.
13. "Speech recognition using a linear dynamic segmental HMM's," in Proc. Eurospeech, 1995, pp. 1611-1614.
14. "Modeling speech variability with segmental HMM's," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1996, pp. 447-450.
15. P. Kenny, M. Lennig, and P. Mermelstein, "A linear predictive HMM for vector valued observation with application to speech recognition," IEEE Trans. Acoust. Speech, Signal Processing, vol. 38, pp. 220-225, 1990.
16. O. Kimball, "Segment modeling alternatives for continuous speech recognition," Ph.D. dissertation, Boston Univ., Boston, MA, 1994.
17. R. G. Leonard, "A database for speaker independent digit recognition," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, Mar. 1984, pp. 42.11.1-44.11.1.
18. M. Ostendorf and S. Roucos, "A stochastic segment model for phonemebased continuous speech recognition," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 1857-1869, 1989.
19. M. Ostendorf and V. Digalakis, "The stochastic segment model for continuous speech recognition," in Proc. 25th Asilomar Conf., Signals, Systems, Computers, 1991, pp. 964-968.
20. M. Ostendorf, V. Digalakis, and O. A. Kimball, "From HMM's to segmentai models: A unified view of stochastic modeling for speech recognition," IEEE Trans. Speech, Audio Processing, vol. 4, pp. 360-377, 1996.
21. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, pp. 257-285, 1989.
22. L. R. Rabiner and B. H. Juang, Fundamentals of Speech Recognition. Englewood Cliffs, NJ: Prentice-Hall, 1993.
23. M. Russell, "A segmental HMM for speech pattern modeling," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1993, pp. 499-502.
24. H. Sakoe and S. Chiba, "Dynamic programming optimization for spoken word recognition," IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-26, pp. 43-49, 1978.
25. R. Schwanz and Y. Chow, "A comparison of several approximate algorithms for finding multiple (jY-best) sentence hypotheses," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1991, pp. 701-704.
26. C. J. Wellekens, "Explicit correlation in hidden Markov models for speech recognition," in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1987, pp. 384-387.