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Volumn 7, Issue 2-3, 2004, Pages 141-153

Accent Issues in Large Vocabulary Continuous Speech Recognition

Author keywords

Accent adaptation; Accent identification; Automatic speech recognition; Pronunciation modeling; Speaker variability

Indexed keywords

COMPUTER SIMULATION; DATA ACQUISITION; DATA REDUCTION; MATHEMATICAL MODELS; SPEECH ANALYSIS;

EID: 1842739879     PISSN: 13812416     EISSN: None     Source Type: Journal    
DOI: 10.1023/b:ijst.0000017014.52972.1d     Document Type: Article
Times cited : (74)

References (23)
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  • 11
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    • Accent modeling based on pronunciation dictionary adaptation for large vocabulary Mandarin speech recognition
    • Huang, C., Chang, E., Zhou, J.L., and Lee, K.P. (2000). Accent modeling based on pronunciation dictionary adaptation for large vocabulary Mandarin speech recognition. Proc. International Conference on Spoken Language Processing, vol. 3, pp. 818-821.
    • (2000) Proc. International Conference on Spoken Language Processing , vol.3 , pp. 818-821
    • Huang, C.1    Chang, E.2    Zhou, J.L.3    Lee, K.P.4
  • 15
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    • Independent component analysis: Algorithms and application
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    • Hyvarinen, A.1    Oja, E.2
  • 16
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    • A study on speaker adaptation of the parameters of continuous density hidden Markov models
    • Lee, C.-H., Lin C.-H., and Juang, B.-H. (1991). A study on speaker adaptation of the parameters of continuous density hidden Markov models. IEEE Transactions on Signal Processing, 39:806-814.
    • (1991) IEEE Transactions on Signal Processing , vol.39 , pp. 806-814
    • Lee, C.-H.1    Lin, C.-H.2    Juang, B.-H.3
  • 17
    • 0029288633 scopus 로고
    • Maximum likely-hood linear regression for speaker adaptation of continuous density hidden Markov models
    • Leggetter, C.J. and Woodland, P.C. (1995). Maximum likely-hood linear regression for speaker adaptation of continuous density hidden Markov models. Computer Speech and Language,9:171-185.
    • (1995) Computer Speech and Language , vol.9 , pp. 171-185
    • Leggetter, C.J.1    Woodland, P.C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.