HMM composition-based rapid model adaptation using a priori noise GMM adaptation evaluation on AURORA2 corpus

7th International Conference on Spoken Language Processing, ICSLP 2002

Volumn , Issue , 2002, Pages 437-440

  Ida, Masaki ^a   Nakamura, Satoshi ^a  

^a ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BASELINE SYSTEMS; COMPOSITION METHOD; GMM ADAPTATIONS; MODEL ADAPTATION; NOCV2; NOISY ENVIRONMENT; REAL ENVIRONMENTS; SPEECH RECOGNITION SYSTEMS; WORD ACCURACIES;

SPEECH RECOGNITION;

EID: 33645769257     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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5. JEIDA Noise Database, http://it.jeita.or.jp/jhistory/committee/humanmed/speech/noisedbe.html
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7. Y Minami and S. Furui, "A maximum likelihood procedure for a universal adaptation method based on HMM composition", Proc. of ICASSP, pp. 129-132, 1995
8. T. Takiguchi, S. Nakamura, and K. Shikano, "HMM-Separation-Based Speech Recognition for a Distant Moving Speaker", IEEE Trans. Speech Audio Processing, Vol. 9, No. 2, pp. 127-140, 2001
9. K. Okuda, T Matsui, and S. Nakamura, "Towards the Creation of Acoustic Models for Stressed Japanese Speech", Proc. of EUROSPEECH, pp. 1653-1656, 2001