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Volumn , Issue , 2011, Pages 2877-2880

Recurrent neural network based language modeling in meeting recognition

Author keywords

Adaptation; Automatic speech recognition; Language modeling; Recurrent neural networks; Rescoring

Indexed keywords

ADAPTATION; AUTOMATIC SPEECH RECOGNITION; DATA SETS; LANGUAGE MODEL; LANGUAGE MODEL ADAPTATION; LANGUAGE MODELING; N-BEST LIST; N-GRAM LANGUAGE MODELS; RESCORING; UNSUPERVISED ADAPTATION; WORD ERROR RATE;

EID: 84865804529     PISSN: None     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (182)

References (12)
  • 4
    • 70450211380 scopus 로고    scopus 로고
    • Investigation into bottle-neck features for meeting speech recognition
    • Brighton, GB. International Speech Communication Association
    • F. Grezl, M. Karafiát and L. Burget. Investigation into bottle-neck features for meeting speech recognition. In Proc. Interspeech 2009, number 9, pages 2947-2950, Brighton, GB, 2009. International Speech Communication Association.
    • (2009) Proc. Interspeech 2009 , Issue.9 , pp. 2947-2950
    • Grezl, F.1    Karafiát, M.2    Burget, L.3
  • 10
    • 79959829092 scopus 로고    scopus 로고
    • Recurrent neural network based language model
    • Makuhari, Chiba, JP. International Speech Communication Association
    • T. Mikolov, M. Karafiát, L. Burget, J. Černocký and S. Khudanpur. Recurrent neural network based language model. In Proc. of INTERSPEECH 2010, number 9, pages 1045-1048, Makuhari, Chiba, JP, 2010. International Speech Communication Association.
    • (2010) Proc. of INTERSPEECH 2010 , Issue.9 , pp. 1045-1048
    • Mikolov, T.1    Karafiát, M.2    Burget, L.3    Černocký, J.4    Khudanpur, S.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.