Impact of single-microphone dereverberation on DNN-based meeting transcription systems
暂无分享,去创建一个
[1] Tomohiro Nakatani,et al. Making Machines Understand Us in Reverberant Rooms: Robustness Against Reverberation for Automatic Speech Recognition , 2012, IEEE Signal Process. Mag..
[2] Petr Fousek,et al. Robust speech recognition using dynamic noise adaptation , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[3] Peder A. Olsen,et al. Dynamic Noise Adaptation , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[4] Khe Chai Sim,et al. Noise adaptive front-end normalization based on Vector Taylor Series for Deep Neural Networks in robust speech recognition , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[5] Jan Cernocký,et al. Probabilistic and Bottle-Neck Features for LVCSR of Meetings , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[6] Andreas G. Andreou,et al. Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition , 1998, Speech Commun..
[7] Mark J. F. Gales,et al. Maximum likelihood linear transformations for HMM-based speech recognition , 1998, Comput. Speech Lang..
[8] Jean Carletta,et al. The AMI Meeting Corpus: A Pre-announcement , 2005, MLMI.
[9] Biing-Hwang Juang,et al. Blind speech dereverberation with multi-channel linear prediction based on short time fourier transform representation , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[10] Yifan Gong,et al. Robust Speech Recognition Using a Cepstral Minimum-Mean-Square-Error-Motivated Noise Suppressor , 2008, IEEE Transactions on Audio, Speech, and Language Processing.
[11] Hervé Bourlard,et al. Connectionist probability estimators in HMM speech recognition , 1994, IEEE Trans. Speech Audio Process..
[12] Xavier Anguera Miró,et al. Acoustic Beamforming for Speaker Diarization of Meetings , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[13] Yongqiang Wang,et al. An investigation of deep neural networks for noise robust speech recognition , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[14] Geoffrey Zweig,et al. fMPE: discriminatively trained features for speech recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[15] Tomohiro Nakatani,et al. Generalization of Multi-Channel Linear Prediction Methods for Blind MIMO Impulse Response Shortening , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[16] Mark J. F. Gales,et al. Model-Based Approaches to Handling Uncertainty , 2011, Robust Speech Recognition of Uncertain or Missing Data.
[17] Mark J. F. Gales,et al. Integrated Online Speaker Clustering and Adaptation , 2011, INTERSPEECH.
[18] Mark J. F. Gales,et al. Semi-tied covariance matrices for hidden Markov models , 1999, IEEE Trans. Speech Audio Process..
[19] Dong Yu,et al. Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[20] Geoffrey E. Hinton,et al. Understanding how Deep Belief Networks perform acoustic modelling , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[21] Dong Yu,et al. Feature engineering in Context-Dependent Deep Neural Networks for conversational speech transcription , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.