QCRI advanced transcription system (QATS) for the Arabic Multi-Dialect Broadcast media recognition: MGB-2 challenge
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[1] Richard M. Schwartz,et al. Practical Implementations of Speaker-Adaptive Training , 1997 .
[2] Andrew W. Senior,et al. Fast and accurate recurrent neural network acoustic models for speech recognition , 2015, INTERSPEECH.
[3] Mark J. F. Gales,et al. The MGB challenge: Evaluating multi-genre broadcast media recognition , 2015, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).
[4] Nizar Habash,et al. MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic , 2014, LREC.
[5] Yiming Wang,et al. Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI , 2016, INTERSPEECH.
[6] Andrew W. Senior,et al. Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.
[7] Florin Curelaru,et al. Front-End Factor Analysis For Speaker Verification , 2018, 2018 International Conference on Communications (COMM).
[8] Sanjeev Khudanpur,et al. A time delay neural network architecture for efficient modeling of long temporal contexts , 2015, INTERSPEECH.
[9] Lukás Burget,et al. Sequence-discriminative training of deep neural networks , 2013, INTERSPEECH.
[10] Sanjeev Khudanpur,et al. Audio augmentation for speech recognition , 2015, INTERSPEECH.
[11] Jan Cernocký,et al. Improved feature processing for deep neural networks , 2013, INTERSPEECH.
[12] Stephan Vogel,et al. Advances in dialectal Arabic speech recognition: a study using Twitter to improve Egyptian ASR , 2014, IWSLT.
[13] M. Picheny,et al. Comparison of Parametric Representation for Monosyllabic Word Recognition in Continuously Spoken Sentences , 2017 .
[14] Mark J. F. Gales,et al. CUED-RNNLM — An open-source toolkit for efficient training and evaluation of recurrent neural network language models , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[15] Tomas Mikolov,et al. RNNLM - Recurrent Neural Network Language Modeling Toolkit , 2011 .
[16] Ramesh A. Gopinath,et al. Maximum likelihood modeling with Gaussian distributions for classification , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[17] Daniel Povey,et al. The Kaldi Speech Recognition Toolkit , 2011 .
[18] Andreas Stolcke,et al. SRILM - an extensible language modeling toolkit , 2002, INTERSPEECH.
[19] Mark J. F. Gales,et al. Maximum likelihood linear transformations for HMM-based speech recognition , 1998, Comput. Speech Lang..