Model complexity adaptation using a discriminant measure

IEEE Transactions on Speech and Audio Processing

Volumn 8, Issue 2, 2000, Pages 205-208

  Padmanabhan, M ^a,b   Bahl, L R ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b Renaissance Technologies   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; ERROR ANALYSIS; MATHEMATICAL MODELS; PATTERN RECOGNITION SYSTEMS; PROBABILITY DENSITY FUNCTION; SPEECH ANALYSIS;

BAYESIAN INFORMATION CRITERION (BIC);

SPEECH RECOGNITION;

EID: 0033884712     PISSN: 10636676     EISSN: None     Source Type: Journal    
DOI: 10.1109/89.824707     Document Type: Article

References (8)

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2. S. S. Chen and P. S. Gopalakrishnan, "Clustering via the Bayesian Information Criterion with applications in speech recognition," in Proc. ICASSP, 1998, pp. 645-648.
3. G. Schwarz, "Estimating the dimension of a model," Ann. Stat., vol. 6, pp. 461-464, 1978.
4. A. Barron, J. Rissanen, and B. Yu, "The minimum description length principle in coding and modeling," IEEE Trans. Inform. Theory, vol. 44, pp. 2743-2760, Oct. 1998.
5. L. R. Bahl and M. Padmanabhan, "A discriminant measure for model complexity estimation," in Proc. ICASSP, 1998, pp. 453-455.
6. Y. Normandin, "Optimal splitting of HMM Gaussian mixture components with MMIE training," in Proc. ICASSP, 1995, pp. 449-452.
7. L. R. Bahl et ai, "Decision trees for phonological rule in continuous speech," in Proc. ICASSP, 1991, pp. 185-188.
8. M. Padmanabhan et al., "Speech recognition performance on a new voicemail transcription task," in Proc. Int. Conf. Spoken Language Processing, 1998, pp. 2475-2478.