Subspace method for minimum error pattern recognition

IEICE Transactions on Information and Systems

Volumn E80-D, Issue 12, 1997, Pages 1195-1204

  Watanabe, Hideyuki ^a   Katagiri, Shigeru ^a  

^a ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

Author keywords

Bayes decision theory; Discriminative training; Gradientdescent search; Minimum recognition error; Subspace method

Indexed keywords

ALGORITHMS; DECISION THEORY; ERRORS; ITERATIVE METHODS; PROBABILITY;

BAYES DECISION THEORY; CLASS FEATURING INFORMATION COMPRESSION; LEARNING SUBSPACE METHOD; MINIMUM ERROR PATTERN RECOGNITION;

PATTERN RECOGNITION;

EID: 0031388365     PISSN: 09168532     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (19)

1. E. Oja, "Subspace Methods of Pattern Recognition," Research Studies Press, 1983.
2. S. Watanabe, P.F. Lambert, C.A. Kulikowski, J.L. Buxton, and R. Walker, "Evaluation and selection of variables in pattern recognition," in Computer and Information Sciences II., ed. J.T. Tou, pp.91122, Academic Press, New York, 1967.
3. T. Kohonen, G. Németh, KJ. Bry, M. Jalanko, and H. Riittinen, "Spectral classification of phonemes by learning subspaces," IEEE Proc. of ICASSP79, pp.97100, April 1979.
4. Y. Ariki and K. Doi, "Speaker recognition based on subspace methods," Proc. of ICSLP94, Yokohama, pp. 18591862, Sept. 1994.
5. Y. Takebayashi, "Speech recognition based on the subspace method: AI classdescription learning viewpoint," J. Acoust. Soc. Jpn. (E), vol.13, no.6, pp.429439, Nov. 1992.
6. R. Duda and P. Hart, "Pattern Classification and Scene Analysis," John Wiley & Sons, 1973.
7. K. Fukunaga, "Introduction to Statistical Pattern Recognition (2nd edition)," Academic Press, 1990.
8. S. Katagiri, C.H. Lee, and B.H. Juang, "New discriminative training algorithms based on the generalized probabilistic descent method," Proc. 1991 IEEE Workshop on Neural Networks for Signal Processing, pp.299308, Princeton, NJ, Sept. 1991.
9. B.H. Juang and S. Katagiri, "Discriminative learning for minimum error classification," IEEE Trans. Signal Processing, vol.40, no.12, pp.30433054, Dec. 1992.
10. B.H. Juang and S. Katagiri, "Discriminative training," J. Acoust. Soc. Jpn. (E), vol.13, no.6, pp.333339, Nov. 1992.
11. E. McDermott and S. Katagiri, "Prototypebased minimum error training for speech recognition," J. of Appl. Int., vol.4, pp.245256, 1994.
12. P.C. Chang and B.H. Juang, "Discriminative training of dynamic programming based speech recognizers," IEEE Trans. SAP, vol.1, no.2, pp.135143, April 1993.
13. W. Chou, B.H. Juang, and C.H. Lee, "Segmental GPD training of HMM based speech recognizer," IEEE Proc. of ICASSP92, vol.1, pp.473476, 1992.
14. D. Rainton and S. Sagayama, "Minimum error classification training of HMMs implementation details and experimental results," J. Acoust. Soc. Jpn. (E), vol.13, no.6, pp.379387, Nov. 1992.
15. W. Chou and B.H. Juang, "Adaptive discriminative learning in pattern recognition," Technical Report of AT&T Bell Laboratory.
16. H. Watanabe and S. Katagiri, "Discriminative subspace method for minimum error pattern recognition," Proc. 1995 IEEE Workshop on Neural Networks for Signal Processing, pp.7786, Sept. 1995.
17. R.J.P. De Figueiredo, "Optimal feature extraction based on the minimization of the increase in risk of misclassification," Proc. IEEE Conf. on Decision and Control (11th Symp. on Adaptive Processes), p.102, 1972.
18. S. Katagiri, "A unified approach to pattern recognition," Proc. of 1994 Int. Sym. Artificial Neural Networks, pp.561570, Dec. 1994.
19. J.R. Blum, "Multidimensional stochastic approximation methods," Ann. Math. Stat., vol.25, pp.737744, 1954.