Cache based recurrent neural network language model inference for first pass speech recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2014, Pages 6354-6358

  Huang, Zhiheng ^a   Zweig, Geoffrey ^b   Dumoulin, Benoit ^a  

^a MICROSOFT   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

cache; computational efficiency; recurrent neural network language model; voice search

Indexed keywords

COMPUTATIONAL EFFICIENCY; COMPUTER AIDED LANGUAGE TRANSLATION; RECURRENT NEURAL NETWORKS; SIGNAL PROCESSING; SPEECH RECOGNITION;

CACHE; COMPUTATIONAL EXPENSE; LANGUAGE PROCESSING; LATTICE RESCORING; MACHINE TRANSLATIONS; N-GRAM MODELING; NETWORK LANGUAGE; VOICE SEARCHES;

COMPUTATIONAL LINGUISTICS;

EID: 84905229914     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2014.6854827     Document Type: Conference Paper

References (16)

1. T. Mikolov, M. Karafiat, L. Burget, J. Cernocky, and S. Khudanpur, "Recurrent neural network based language model," in INTERSPEECH, 2010.
2. M. Auli, M. Galley, C. Quirk, and G. Zweig, "Joint language and translation modeling with recurrent neural networks," in EMNLP, 2013.
3. G. Mesnil, X. He, L. Deng, and Y. Bengio, "Investigation of recurrent-neural-network architectures and learning methods for language understanding," in INTERSPEECH, 2013.
4. K. Yao, G. Zweig, M. Hwang, Y. Shi, and Dong Yu, "Recurrent neural networks for language understanding," in INTERSPEECH, 2013.
5. T. Mikolov, S. Kombrink, L. Burget, J. H. Cernocky, and S. Khudanpur, "Extensions of recurrent neural network language model," in ICASSP, 2011.
6. A. Deoras, T. M. Mikolov, S. Kombrink, M. Karafiat, and S. Khudanpur, "Variational approximation of longspan language models for lvcsr," in ICASSP, 2011.
7. G. Lecorve and P. Motlicek, "Conversion of recurrent neural network language models to weighted finite state transducers for automatic speech recognition," in Interspeech, 2012.
8. E. Arisoy, S. F. Chen, B. Ramabhadran, and A. Sethy, "Converting neural network language models into backoff language models for efficient decoding in automatic speech recognition," in Interspeech, 2013.
9. S. Kombrink, T. Mikolov, M. Karafiat, and L. Burget, "Recurrent neural network based language modeling in meeting recognition," in INTERSPEECH, 2011.
10. Y. Si, Q. Zhang, T. Li, J. Pan, and Y. Yan, "Prefix tree based n-best list rescoring for recurrent neural network language model used in speech recognition system," in Interspeech, 2013.
11. T. Mikolov, A. Deoras, D. Povey, L. Burget, and J. H. Cernocky, "Strategies for training large scale neural network languge models," in ASRU, 2011.
12. G. Zweig and K. Makarychev, "Speed regularization and optimality in word classing," in ICASSP, 2013.
13. H. Soltau and G. Saon, "Dynamic network decoding revised," in ASRU, 2009.
14. G. Zweig and S. Chang, "Personalizing model m for voice-search," in INTERSPEECH, 2011.
15. Y. Shi, P. Wiggers, and C. M. Jonker, "Towards recurrent neural networks language models with linguistic and contextual features," in INTERSPEECH, 2012.
16. T. Mikolov and G. Zweig, "Context dependent recurrent neural network language model," in SLT, 2012.