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Volumn , Issue , 2006, Pages 1249-1256

Large Margin Hidden Markov Models for Automatic Speech Recognition

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONVEX OPTIMIZATION; SPEECH RECOGNITION; SUPPORT VECTOR MACHINES; TRELLIS CODES;

EID: 85078843680     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (19)

References (21)
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    • MMI training for continuous phoneme recognition on the TIMIT database
    • pages Minneapolis, MN
    • S. Kapadia, V. Valtchev, and S. Young. MMI training for continuous phoneme recognition on the TIMIT database. In Proc. of ICASSP 93, volume 2, pages 491-494, Minneapolis, MN, 1993.
    • (1993) Proc. of ICASSP 93 , vol.2 , pp. 491-494
    • Kapadia, S.1    Valtchev, V.2    Young, S.3
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    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilisitc models for segmenting and labeling sequence data
    • Morgan Kaufmann, San Francisco, CA
    • J. Lafferty, A. McCallum, and F. C. N. Pereira. Conditional random fields: Probabilisitc models for segmenting and labeling sequence data. In Proc. 18th International Conf. on Machine Learning (ICML 2001), pages 282-289. Morgan Kaufmann, San Francisco, CA, 2001.
    • (2001) Proc. 18th International Conf. on Machine Learning (ICML 2001) , pp. 282-289
    • Lafferty, J.1    McCallum, A.2    Pereira, F. C. N.3
  • 7
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    • Speech database development: design and analsysis of the acoustic-phonetic corpus
    • L. S. Baumann, editor, pages
    • L. F. Lamel, R. H. Kassel, and S. Seneff. Speech database development: design and analsysis of the acoustic-phonetic corpus. In L. S. Baumann, editor, Proceedings of the DARPA Speech Recognition Workshop, pages 100-109, 1986.
    • (1986) Proceedings of the DARPA Speech Recognition Workshop , pp. 100-109
    • Lamel, L. F.1    Kassel, R. H.2    Seneff, S.3
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    • 33646799820 scopus 로고    scopus 로고
    • Large margin HMMs for speech recognition
    • Philadelphia
    • X. Li, H. Jiang, and C. Liu. Large margin HMMs for speech recognition. In Proceedings of ICASSP 2005, pages 513-516, Philadelphia, 2005.
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    • Li, X.1    Jiang, H.2    Liu, C.3
  • 11
    • 0020796537 scopus 로고
    • A decision-theoretic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood
    • A. Nádas. A decision-theoretic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood. IEEE Transactions on Acoustics, Speech and Signal Processing, 31(4):814-817, 1983.
    • (1983) IEEE Transactions on Acoustics, Speech and Signal Processing , vol.31 , Issue.4 , pp. 814-817
    • Nádas, A.1
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    • 33947686745 scopus 로고    scopus 로고
    • Large margin Gaussian mixture modeling for phonetic classification and recognition
    • Toulouse, France
    • F. Sha and L. K. Saul. Large margin Gaussian mixture modeling for phonetic classification and recognition. In Proceedings of ICASSP 2006, pages 265-268, Toulouse, France, 2006.
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    • Sha, F.1    Saul, L. K.2
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    • Comparison of large margin training to other discriminative methods for phonetic recognition by hidden Markov models
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.