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Volumn , Issue , 2012, Pages 41-49

Large-scale discriminative language model reranking for voice-search

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; CONTINUOUS SPEECH RECOGNITION;

EID: 84902303733     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (15)
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    • Brants, T.1    Popat, A.C.2    Xu, P.3    Och, F.J.4    Dean, J.5
  • 4
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms
    • M. Collins. 2002. Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. In Proc. EMNLP.
    • (2002) Proc. EMNLP.
    • Collins, M.1
  • 5
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    • Minimum sample risk methods for language modeling
    • J. Gao, H. Yu, W. Yuan, and P. Xu. 2005. Minimum sample risk methods for language modeling. In Proc. of EMNLP.
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    • Gao, J.1    Yu, H.2    Yuan, W.3    Xu, P.4
  • 6
    • 85030321143 scopus 로고    scopus 로고
    • Mapreduce: Simplified data processing on large clusters
    • S. Ghemawat and J. Dean. 2004. Mapreduce: Simplified data processing on large clusters. In Proc. OSDI.
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    • Ghemawat, S.1    Dean, J.2
  • 8
    • 79959849984 scopus 로고    scopus 로고
    • Discriminative language modeling using simulated ASR errors
    • P. Jyothi and E. Fosler-Lussier. 2010. Discriminative language modeling using simulated ASR errors. In Proc. of Interspeech.
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    • Jyothi, P.1    Fosler-Lussier, E.2
  • 9
    • 84867619356 scopus 로고    scopus 로고
    • Distributed discriminative language models for Google voice-search
    • P. Jyothi, L. Johnson, C. Chelba, and B. Strope. 2012. Distributed discriminative language models for Google voice-search. In Proc. of ICASSP.
    • (2012) Proc. Of ICASSP.
    • Jyothi, P.1    Johnson, L.2    Chelba, C.3    Strope, B.4
  • 10
    • 80052652249 scopus 로고    scopus 로고
    • Efficient large-scale distributed training of conditional maximum entropy models
    • G. Mann, R. McDonald, M. Mohri, N. Silberman, and D. Walker. 2009. Efficient large-scale distributed training of conditional maximum entropy models. Proc. NIPS.
    • (2009) Proc. NIPS.
    • Mann, G.1    McDonald, R.2    Mohri, M.3    Silberman, N.4    Walker, D.5
  • 11
    • 80052650170 scopus 로고    scopus 로고
    • Distributed training strategies for the structured perceptron
    • R. McDonald, K. Hall, and G. Mann. 2010. Distributed training strategies for the structured perceptron. In Proc. NAACL.
    • (2010) Proc. NAACL.
    • McDonald, R.1    Hall, K.2    Mann, G.3
  • 12
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    • Discriminative language modeling with conditional random fields and the perceptron algorithm
    • B. Roark, M. Saraçlar, M. Collins, and M. Johnson. 2004. Discriminative language modeling with conditional random fields and the perceptron algorithm. In Proc. ACL.
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    • A comparative study of discriminative methods for reranking LVCSR N-best hypotheses in domain adaptation and generalization
    • Z. Zhou, J. Gao, F.K. Soong, and H. Meng. 2006. A comparative study of discriminative methods for reranking LVCSR N-best hypotheses in domain adaptation and generalization. In Proc. ICASSP.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.