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Volumn 25, Issue 1-3, 1998, Pages 133-147

Cepstral domain segmental feature vector normalization for noise robust speech recognition

Author keywords

Feature vector normalization; Noise robustness; Speech recognition

Indexed keywords

ACOUSTIC NOISE; ERROR COMPENSATION; PARAMETER ESTIMATION; PERFORMANCE; ROBUSTNESS (CONTROL SYSTEMS); SPEECH PROCESSING;

EID: 0032141206     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-6393(98)00033-8     Document Type: Article
Times cited : (299)

References (16)
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    • Gales, M.J.F.1    Young, S.2
  • 6
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    • Perceptual Linear Predictive (PLP) analysis of speech
    • Hermansky, H., 1990. Perceptual Linear Predictive (PLP) analysis of speech. J. Acoust. Soc. Amer. 87 (4), 1738-1752.
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    • Hermansky, H.1
  • 8
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    • Experiments with a Nonlinear Spectral Subtractor (NSS), Hidden Markov Models and the projection, for robust speech recognition in cars
    • Lockwood, P., Boudy, J., 1992. Experiments with a Nonlinear Spectral Subtractor (NSS), Hidden Markov Models and the projection, for robust speech recognition in cars. Speech Communication 11 (2-3), 215-228.
    • (1992) Speech Communication , vol.11 , Issue.2-3 , pp. 215-228
    • Lockwood, P.1    Boudy, J.2
  • 13
    • 85135190755 scopus 로고    scopus 로고
    • Multi-band and adaptation approaches to robust speech recognition
    • Tibrewala, S., Hermansky, H., 1997. Multi-band and adaptation approaches to robust speech recognition, Proceedings of the EUROSPEECH, Vol. 5, pp. 2619-2622.
    • (1997) Proceedings of the EUROSPEECH , vol.5 , pp. 2619-2622
    • Tibrewala, S.1    Hermansky, H.2
  • 16
    • 0347387895 scopus 로고
    • Dynamic parameter compensation for speech recognition in noise
    • Yang, R., Majaniemi, M., Haavisto, P., 1995. Dynamic parameter compensation for speech recognition in noise, Proceedings of the EUROSPEECH, Vol. 1, pp. 469-472.
    • (1995) Proceedings of the EUROSPEECH , vol.1 , pp. 469-472
    • Yang, R.1    Majaniemi, M.2    Haavisto, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.