Ariya Rastrow, Ph.D.

Affiliations: 
2012 Johns Hopkins University, Baltimore, MD 
Area:
Electronics and Electrical Engineering, Computer Science
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"Ariya Rastrow"

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Sanjeev Khudanpur grad student 2012 Johns Hopkins
 (Practical and efficient incorporation of syntactic features into statistical language models.)
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Publications

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Rastrow A, Dredze M, Khudanpur S. (2012) Efficient structured language modeling for speech recognition 13th Annual Conference of the International Speech Communication Association 2012, Interspeech 2012. 2: 1658-1661
Rastrow A, Dredze M, Khudanpur S. (2012) Fast syntactic analysis for statistical language modeling via substructure sharing and uptraining 50th Annual Meeting of the Association For Computational Linguistics, Acl 2012 - Proceedings of the Conference. 1: 175-183
Rastrow A, Dredze M, Khudanpur S. (2011) Adapting n-gram maximum entropy language models with conditional entropy regularization 2011 Ieee Workshop On Automatic Speech Recognition and Understanding, Asru 2011, Proceedings. 220-225
Rastrow A, Dredze M, Khudanpur S. (2011) Efficient discriminative training of long-span language models 2011 Ieee Workshop On Automatic Speech Recognition and Understanding, Asru 2011, Proceedings. 214-219
Povey D, Burget L, Agarwal M, et al. (2010) Subspace gaussian mixture models for speech recognition Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 4330-4333
Ghoshal A, Povey D, Agarwal M, et al. (2010) A novel estimation of feature-space MLLR for full-covariance models Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 4310-4313
Burget L, Schwarz P, Agarwal M, et al. (2010) Multilingual acoustic modeling for speech recognition based on subspace Gaussian mixture models Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 4334-4337
Goel N, Thomas S, Agarwal M, et al. (2010) Approaches to automatic lexicon learning with limited training examples Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 5094-5097
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