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Volumn 41, Issue 2-3, 2003, Pages 369-379

Multi-class composite N-gram language model

Author keywords

Class N gram; N gram language model; Variable length N gram; Word clustering

Indexed keywords

COMPUTATIONAL METHODS; SPEECH RECOGNITION; STATISTICAL METHODS;

EID: 0038373395     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-6393(02)00179-6     Document Type: Article
Times cited : (41)

References (11)
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  • 3
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  • 4
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    • Katz, S.M.1
  • 5
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    • Variable-order N -gram generation by word-class splitting and consecutive word grouping
    • Masataki, H., Matsunaga, S., Sagisaka, Y., 1996. Variable-order N -gram generation by word-class splitting and consecutive word grouping. In: Proc. ICASSP, pp. 188-191.
    • (1996) Proc. ICASSP , pp. 188-191
    • Masataki, H.1    Matsunaga, S.2    Sagisaka, Y.3
  • 6
    • 0030715097 scopus 로고    scopus 로고
    • HMM topology design using maximum likelihood successive state splitting
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    • Ostendorf, M.1    Singer, H.2
  • 7
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    • Spontaneous dialogue speech recognition using cross-word context constrained word graphs
    • Shimizu, T., Yamamoto, H., Masataki, H., Matsunaga, S., Sagisaka, Y., 1996. Spontaneous dialogue speech recognition using cross-word context constrained word graphs. In: Proc. ICASSP, pp. 145-148.
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    • Shimizu, T.1    Yamamoto, H.2    Masataki, H.3    Matsunaga, S.4    Sagisaka, Y.5
  • 9
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    • Hierachical grouping to optimize an objective function
    • Ward J.H. Jr. Hierachical grouping to optimize an objective function. J. Amer. Statist. Assoc. 58:1963;236-244.
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    • Ward J.H., Jr.1
  • 10
    • 0032626587 scopus 로고    scopus 로고
    • Multi-class composite N -gram based on connection direction
    • Yamamoto, H., Sagisaka, Y., 1999. Multi-class composite N -gram based on connection direction. In: Proc. ICASSP, pp. 533-536.
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    • Yamamoto, H.1    Sagisaka, Y.2
  • 11
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    • Improving N -gram modeling using distance-related unit association maximum entropy language modeling
    • Zhang, S., Singer, H., Wu, D., Sagisaka, Y., 1999. Improving N -gram modeling using distance-related unit association maximum entropy language modeling. In: Proc. EuroSpeech, pp. 1611-1614.
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    • Zhang, S.1    Singer, H.2    Wu, D.3    Sagisaka, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.