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Volumn , Issue , 2013, Pages 3092-3096

Neural network acoustic models for the DARPA RATS program

Author keywords

Convolutional neural network; Multi layer perceptron; Time delay neural network

Indexed keywords

NEURAL NETWORKS;

EID: 84906257050     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (28)

References (22)
  • 1
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    • Conversational speech transcription using context-dependent deep neural networks
    • F. Seide, G. Li, and D. Yu, "Conversational speech transcription using context-dependent deep neural networks, " in Interspeech, 2011.
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    • Seide, F.1    Li, G.2    Yu, D.3
  • 4
    • 84858976070 scopus 로고    scopus 로고
    • Feature engineering in context-dependent deep neural networks for conversational speech transcription
    • F. Seide, G. Li, X. Chen, and D. Yu, "Feature engineering in context-dependent deep neural networks for conversational speech transcription, " in Proc. ASRU, 2011.
    • (2011) Proc. ASRU
    • Seide, F.1    Li, G.2    Chen, X.3    Yu, D.4
  • 6
    • 84878607780 scopus 로고    scopus 로고
    • LDC2006S29, arabic CTS levantine QT training data set 5
    • M. Maamouri et al., "LDC2006S29, Arabic CTS Levantine QT training data set 5, " in Linguistic Data Consortium, 2006.
    • (2006) Linguistic Data Consortium
    • Maamouri, M.1
  • 11
    • 84862277874 scopus 로고    scopus 로고
    • Understanding the difficulty of training deep feedforward neural networks
    • X. Glorot and Y. Bengio, "Understanding the difficulty of training deep feedforward neural networks, " in Proc. AISTATS, 2010, pp. 249-256.
    • (2010) Proc. AISTATS , pp. 249-256
    • Glorot, X.1    Bengio, Y.2
  • 12
    • 84858972572 scopus 로고    scopus 로고
    • Making deep belief networks effective for large vocabulary continuous speech recognition
    • submitted
    • T. Sainath, B. Kingsbury, B. Ramabhadran, P. Fousek, P. Novak, and A. Mohamed, "Making deep belief networks effective for large vocabulary continuous speech recognition, " in Proc. ASRU, 2011, submitted.
    • (2011) Proc. ASRU
    • Sainath, T.1    Kingsbury, B.2    Ramabhadran, B.3    Fousek, P.4    Novak, P.5    Mohamed, A.6
  • 16
    • 70349213445 scopus 로고    scopus 로고
    • Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling
    • B. Kingsbury, "Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling, " in Proc. ICASSP, 2009.
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    • Kingsbury, B.1
  • 17
    • 84878379108 scopus 로고    scopus 로고
    • Scalable minimum Bayes risk training of neural network acoustic models using distributed Hessian-free optimization
    • B. Kingsbury, T. N. Sainath, and H. Soltau, "Scalable minimum Bayes risk training of neural network acoustic models using distributed Hessian-free optimization, " in Proc. Interspeech, 2012.
    • (2012) Proc. Interspeech
    • Kingsbury, B.1    Sainath, T.N.2    Soltau, H.3
  • 18
    • 77956541496 scopus 로고    scopus 로고
    • Deep learning via Hessian-free optimization
    • J. Martens, "Deep learning via Hessian-free optimization, " in Proc. ICML, 2010.
    • (2010) Proc. ICML
    • Martens, J.1
  • 21
    • 84867605836 scopus 로고    scopus 로고
    • Applying convolutional neural network concepts to hybrid NN-HMM model for speech recognition
    • O. Abdel-Hamid, A. Mohamed, H. Jiang, and G. Penn, "Applying convolutional neural network concepts to hybrid NN-HMM model for speech recognition, " in Proc. ICASSP, 2012.
    • (2012) Proc. ICASSP
    • Abdel-Hamid, O.1    Mohamed, A.2    Jiang, H.3    Penn, G.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.