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Volumn , Issue , 2014, Pages 830-834

Distributed learning of multilingual DNN feature extractors using GPUs

Author keywords

Automatic speech recognition; Deep neural networks; Distributed learning

Indexed keywords

PROGRAM PROCESSORS; SPEECH COMMUNICATION; STOCHASTIC SYSTEMS;

EID: 84910068044     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (19)

References (32)
  • 1
    • 84055222005 scopus 로고    scopus 로고
    • Contextdependent pre-trained deep neural networks for large vocabulary speech recognition
    • G. Dahl, D. Yu, L. Deng, and A. Acero, "Contextdependent pre-trained deep neural networks for large vocabulary speech recognition, " IEEE Transactions on Audio, Speech and Language Processing, vol. 20(1), pp. 30-42, 2012.
    • (2012) IEEE Transactions on Audio, Speech and Language Processing , vol.20 , Issue.1 , pp. 30-42
    • Dahl, G.1    Yu, D.2    Deng, L.3    Acero, A.4
  • 2
    • 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, pp. 24-29, 2011.
    • (2011) Proc. ASRU , pp. 24-29
    • Seide, F.1    Li, G.2    Chen, X.3    Yu, D.4
  • 3
    • 84910031119 scopus 로고    scopus 로고
    • Towards speaker adaptive training of deep neural network acoustic models
    • Y. Miao, H. Zhang, and F. Metze, "Towards speaker adaptive training of deep neural network acoustic models, " to appear in Proc. Interspeech, 2014.
    • (2014) Proc. Interspeech
    • Miao, Y.1    Zhang, H.2    Metze, F.3
  • 4
    • 84906273501 scopus 로고    scopus 로고
    • Improving low-resource CDDNN- HMM using dropout and multilingual DNN training
    • Y. Miao, and F. Metze, "Improving low-resource CDDNN- HMM using dropout and multilingual DNN training, " in Proc. Interspeech, pp. 2237-2241, 2013.
    • (2013) Proc. Interspeech , pp. 2237-2241
    • Miao, Y.1    Metze, F.2
  • 5
    • 84893701756 scopus 로고    scopus 로고
    • Deep maxout networks for low-resource speech recognition
    • Y. Miao, F. Metze, and S. Rawat, "Deep maxout networks for low-resource speech recognition, " in Proc. ASRU, 2013.
    • (2013) Proc. ASRU
    • Miao, Y.1    Metze, F.2    Rawat, S.3
  • 6
    • 84874278045 scopus 로고    scopus 로고
    • Unsupervised cross-lingual knowledge transfer in DNNbased LVCSR
    • P. Swietojanski, A. Ghoshal, and S. Renals, "Unsupervised cross-lingual knowledge transfer in DNNbased LVCSR, " in Proc. SLT, pp. 246-251, 2012.
    • (2012) Proc. SLT , pp. 246-251
    • Swietojanski, P.1    Ghoshal, A.2    Renals, S.3
  • 7
    • 84878559540 scopus 로고    scopus 로고
    • An investigation on initialization schemes for multilayer perceptron training using multilingual data and their effect on ASR performance
    • N. T. Vu, W. Breiter, F. Metze, and T. Schultz, "An investigation on initialization schemes for multilayer perceptron training using multilingual data and their effect on ASR performance, " in Proc. Interspeech, 2012.
    • (2012) Proc. Interspeech
    • Vu, N.T.1    Breiter, W.2    Metze, F.3    Schultz, T.4
  • 9
    • 84890527497 scopus 로고    scopus 로고
    • Crosslanguage knowledge transfer using multilingual deep neural network with shared hidden layers
    • J.-T. Huang, J. Li, D. Yu, L. Deng, and Y. Gong, "Crosslanguage knowledge transfer using multilingual deep neural network with shared hidden layers, " in Proc. ICASSP, pp. 7304-7308, 2013.
    • (2013) Proc. ICASSP , pp. 7304-7308
    • Huang, J.-T.1    Li, J.2    Yu, D.3    Deng, L.4    Gong, Y.5
  • 10
    • 84905239342 scopus 로고    scopus 로고
    • Improving deep neural network acoustic models using generalized maxout networks
    • X. Zhang, J. Trmal, D. Povey, and S. Khudanpur, "Improving deep neural network acoustic models using generalized maxout networks, " in Proc. ICASSP, 2014.
    • (2014) Proc. ICASSP
    • Zhang, X.1    Trmal, J.2    Povey, D.3    Khudanpur, S.4
  • 12
    • 84878397276 scopus 로고    scopus 로고
    • Pipelined back-propagation for context-dependent deep neural networks
    • X. Chen, A. Eversole, G. Li, D. Yu, and F. Seide, "Pipelined back-propagation for context-dependent deep neural networks, " in Proc. Interspeech, 2012.
    • (2012) Proc. Interspeech
    • Chen, X.1    Eversole, A.2    Li, G.3    Yu, D.4    Seide, F.5
  • 13
    • 84890512601 scopus 로고    scopus 로고
    • Asynchronous stochastic gradient descent for DNN training
    • S. Zhang, C. Zhang, Z. You, R. Zheng, and B. Xu, "Asynchronous stochastic gradient descent for DNN training, " in Proc. ICASSP, pp. 6660-6663, 2013.
    • (2013) Proc. ICASSP , pp. 6660-6663
    • Zhang, S.1    Zhang, C.2    You, Z.3    Zheng, R.4    Xu, B.5
  • 17
    • 84910028405 scopus 로고    scopus 로고
    • Improving language-universal feature extraction with deep maxout and convolutional neural networks
    • Y. Miao, and F. Metze, "Improving language-universal feature extraction with deep maxout and convolutional neural networks, " to appear in Proc. Interspeech, 2014.
    • (2014) Proc. Interspeech
    • Miao, Y.1    Metze, F.2
  • 18
    • 84890495545 scopus 로고    scopus 로고
    • Subspace mixture model for low-resource speech recognition in crosslingual settings
    • Y. Miao, F. Metze, and A. Waibel, "Subspace mixture model for low-resource speech recognition in crosslingual settings, " in Proc. ICASSP, pp. 7339-7342, 2013.
    • (2013) Proc. ICASSP , pp. 7339-7342
    • Miao, Y.1    Metze, F.2    Waibel, A.3
  • 19
    • 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. D. Walker, "Efficient large-scale distributed training of conditional maximum entropy models, " in Proc. NIPS, 2009.
    • (2009) Proc. NIPS
    • Mann, G.1    Mcdonald, R.2    Mohri, M.3    Silberman, N.4    Walker, D.D.5
  • 20
    • 84910080310 scopus 로고    scopus 로고
    • Asynchronous distributed learning of topic models
    • A. Asuncion, P. Smyth, and M. Welling, "Asynchronous distributed learning of topic models, " in Proc. NIPS, 2012.
    • (2012) Proc. NIPS
    • Asuncion, A.1    Smyth, P.2    Welling, M.3
  • 22
    • 79251574977 scopus 로고    scopus 로고
    • The efficient incorporation of MLP features into automatic speech recognition systems
    • J. Park, F. Diehl, M.J.F. Gales, M. Tomalin, and P.C. Woodland, "The efficient incorporation of MLP features into automatic speech recognition systems, " Computer Speech and Language, volume 25, issue 3, pp. 519-534, 2011.
    • (2011) Computer Speech and Language , vol.25 , Issue.3 , pp. 519-534
    • Park, J.1    Diehl, F.2    Gales, M.J.F.3    Tomalin, M.4    Woodland, P.C.5
  • 24
    • 84878582419 scopus 로고    scopus 로고
    • Cross-lingual and ensemble MLPs strategies for low-resource speech recognition
    • Y. Qian, and J. Liu, "Cross-lingual and ensemble MLPs strategies for low-resource speech recognition, " in Proc. Interspeech, 2012.
    • (2012) Proc. Interspeech
    • Qian, Y.1    Liu, J.2
  • 25
    • 84890482429 scopus 로고    scopus 로고
    • Extracting deep bottleneck features using stacked autoencoders
    • J. Gehring, Y. Miao, F. Metze, and A. Waibel, "Extracting deep bottleneck features using stacked autoencoders, " in Proc. ICASSP, pp. 3377-3381, 2013.
    • (2013) Proc. ICASSP , pp. 3377-3381
    • Gehring, J.1    Miao, Y.2    Metze, F.3    Waibel, A.4
  • 27
    • 84906283232 scopus 로고    scopus 로고
    • Using conversational word bursts in spoken term detection
    • J. Chiu, and A. Rudnicky, "Using conversational word bursts in spoken term detection, " in Proc. Interspeech, 2013.
    • (2013) Proc. Interspeech
    • Chiu, J.1    Rudnicky, A.2
  • 29
    • 0032050110 scopus 로고    scopus 로고
    • Maximum likelihood linear transformations for HMM-based speech recognition
    • M. Gales, "Maximum likelihood linear transformations for HMM-based speech recognition, " Computer Speech and Language, vol. 12, pp. 75-98, 1998.
    • (1998) Computer Speech and Language , vol.12 , pp. 75-98
    • Gales, M.1
  • 31
    • 84867605836 scopus 로고    scopus 로고
    • Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition
    • O. Abdel-Hamid, A. Mohamed, H. Jiang, and G. Penn, "Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition, " in Proc. ICASSP, pp. 4277-4280, 2012.
    • (2012) Proc. ICASSP , pp. 4277-4280
    • Abdel-Hamid, O.1    Mohamed, A.2    Jiang, H.3    Penn, G.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.