Model-Based Approaches to Handling Uncertainty

[1]  W. Marsden I and J , 2012 .

[2]  M. Gales,et al.  Adaptive Training and Noise Estimation for Model-Based Noise Compensation for ASR , 2012 .

[3]  Mark J. F. Gales,et al.  Noisy Constrained Maximum-Likelihood Linear Regression for Noise-Robust Speech Recognition , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[4]  Mark J. F. Gales,et al.  Extended VTS for Noise-Robust Speech Recognition , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[5]  Mark J. F. Gales,et al.  Discriminative classifiers with adaptive kernels for noise robust speech recognition , 2010, Comput. Speech Lang..

[6]  Mark J. F. Gales,et al.  Asymptotically exact noise-corrupted speech likelihoods , 2010, INTERSPEECH.

[7]  Alex Acero,et al.  Acoustic model adaptation via Linear Spline Interpolation for robust speech recognition , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[8]  Mark J. F. Gales,et al.  Improving joint uncertainty decoding performance by predictive methods for noise robust speech recognition , 2009, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding.

[9]  Mark J. F. Gales,et al.  Discriminative adaptive training with VTS and JUD , 2009, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding.

[10]  Mark J. F. Gales,et al.  Adaptive training with noisy constrained maximum likelihood linear regression for noise robust speech recognition , 2009, INTERSPEECH.

[11]  Mark J. F. Gales,et al.  Transforming features to compensate speech recogniser models for noise , 2009, INTERSPEECH.

[12]  Alex Acero,et al.  Noise adaptive training using a vector taylor series approach for noise robust automatic speech recognition , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Masami Akamine,et al.  Bayesian feature enhancement using a mixture of unscented transformation for uncertainty decoding of noisy speech , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[14]  Mark J. F. Gales,et al.  Incremental predictive and adaptive noise compensation , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[15]  Xiaodong Cui,et al.  Stereo-Based Stochastic Mapping for Robust Speech Recognition , 2009, IEEE Transactions on Audio, Speech, and Language Processing.

[16]  Reinhold Häb-Umbach,et al.  An analytic derivation of a phase-sensitive observation model for noise robust speech recognition , 2009, INTERSPEECH.

[17]  Yifan Gong,et al.  HMM adaptation using a phase-sensitive acoustic distortion model for environment-robust speech recognition , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[18]  Mark J. F. Gales,et al.  Issues with uncertainty decoding for noise robust automatic speech recognition , 2008, Speech Commun..

[19]  Mark J. F. Gales,et al.  Predictive linear transforms for noise robust speech recognition , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

[20]  Mark J. F. Gales,et al.  Adaptive Training with Joint Uncertainty Decoding for Robust Recognition of Noisy Data , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[21]  Yifan Gong,et al.  High-performance hmm adaptation with joint compensation of additive and convolutive distortions via Vector Taylor Series , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

[22]  Yu Hu,et al.  Irrelevant variability normalization based HMM training using VTS approximation of an explicit model of environmental distortions , 2007, INTERSPEECH.

[23]  Jonathan Le Roux,et al.  Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[24]  Mark J. F. Gales,et al.  The Application of Hidden Markov Models in Speech Recognition , 2007, Found. Trends Signal Process..

[25]  Yu Hu,et al.  An HMM Compensation Approach Using Unscented Transformation for Noisy Speech Recognition , 2006, ISCSLP.

[26]  Mark J. F. Gales,et al.  Issues with uncertainty decoding for noise robust speech recognition , 2006, INTERSPEECH.

[27]  Hank Liao,et al.  Joint uncertainty decoding for robust large vocabulary speech recognition , 2006 .

[28]  R.M. Stern,et al.  Missing-feature approaches in speech recognition , 2005, IEEE Signal Processing Magazine.

[29]  Mark J. F. Gales,et al.  Joint uncertainty decoding for noise robust speech recognition , 2005, INTERSPEECH.

[30]  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..

[31]  Hugo Van hamme,et al.  Effect of phase-sensitive environment model and higher order VTS on noisy speech feature enhancement [speech recognition applications] , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[32]  S. Sagayama,et al.  Maximum likelihood based HMM state filtering approach to model adaptation for long reverberation , 2005, IEEE Workshop on Automatic Speech Recognition and Understanding, 2005..

[33]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[34]  Hugo Van hamme,et al.  Accounting for the uncertainty of speech estimates in the context of model-based feature enhancement , 2004, INTERSPEECH.

[35]  Richard M. Stern,et al.  A Bayesian classifier for spectrographic mask estimation for missing feature speech recognition , 2004, Speech Commun..

[36]  Li Deng,et al.  Enhancement of log Mel power spectra of speech using a phase-sensitive model of the acoustic environment and sequential estimation of the corrupting noise , 2004, IEEE Transactions on Speech and Audio Processing.

[37]  Jean Paul Haton,et al.  Statistical adaptation of acoustic models to noise conditions for robust speech recognition , 2002, INTERSPEECH.

[38]  Mark A. Clements,et al.  Using observation uncertainty in HMM decoding , 2002, INTERSPEECH.

[39]  Li Deng,et al.  Uncertainty decoding with SPLICE for noise robust speech recognition , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[40]  Brendan J. Frey,et al.  Speech recognition in adverse environments: a probabilistic approach , 2002 .

[41]  Brendan J. Frey,et al.  ALGONQUIN: iterating laplace's method to remove multiple types of acoustic distortion for robust speech recognition , 2001, INTERSPEECH.

[42]  Alex Acero,et al.  Spoken Language Processing , 2001 .

[43]  Li Deng,et al.  HMM adaptation using vector taylor series for noisy speech recognition , 2000, INTERSPEECH.

[44]  Li Deng,et al.  Large-vocabulary speech recognition under adverse acoustic environments , 2000, INTERSPEECH.

[45]  Mark J. F. Gales Cluster adaptive training of hidden Markov models , 2000, IEEE Trans. Speech Audio Process..

[46]  Wu Chou,et al.  Maximum a posterior linear regression with elliptically symmetric matrix variate priors , 1999, EUROSPEECH.

[47]  Mark J. F. Gales,et al.  Semi-tied covariance matrices for hidden Markov models , 1999, IEEE Trans. Speech Audio Process..

[48]  Bhuvana Ramabhadran,et al.  Factor analysis invariant to linear transformations of data , 1998, ICSLP.

[49]  Mark J. F. Gales,et al.  Maximum likelihood linear transformations for HMM-based speech recognition , 1998, Comput. Speech Lang..

[50]  Chong Kwan Un,et al.  Speech recognition in noisy environments using first-order vector Taylor series , 1998, Speech Commun..

[51]  Satoshi Takahashi,et al.  Jacobian approach to fast acoustic model adaptation , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[52]  Richard M. Schwartz,et al.  A compact model for speaker-adaptive training , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[53]  Mark J. F. Gales,et al.  Mean and variance adaptation within the MLLR framework , 1996, Comput. Speech Lang..

[54]  Li Lee,et al.  Speaker normalization using efficient frequency warping procedures , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[55]  Chin-Hui Lee,et al.  A maximum-likelihood approach to stochastic matching for robust speech recognition , 1996, IEEE Trans. Speech Audio Process..

[56]  Mark J. F. Gales,et al.  Model-based techniques for noise robust speech recognition , 1995 .

[57]  Michael Picheny,et al.  Robust speech recognition in noise --- performance of the IBM continuous speech recogniser on the ARPA noise spoke task , 1995 .

[58]  Vassilios Digalakis,et al.  Speaker adaptation using constrained estimation of Gaussian mixtures , 1995, IEEE Trans. Speech Audio Process..

[59]  Sadaoki Furui,et al.  A maximum likelihood procedure for a universal adaptation method based on HMM composition , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[60]  Philip C. Woodland,et al.  Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models , 1995, Comput. Speech Lang..

[61]  Leonardo Neumeyer,et al.  Probabilistic optimum filtering for robust speech recognition , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[62]  Saeed Vaseghi,et al.  Speech recognition in noisy environments , 1992, ICSLP.

[63]  Alejandro Acero,et al.  Acoustical and environmental robustness in automatic speech recognition , 1991 .

[64]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[65]  Roger K. Moore,et al.  Noise compensation algorithms for use with hidden Markov model based speech recognition , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[66]  Lawrence R. Rabiner,et al.  A tutorial on Hidden Markov Models , 1986 .

[67]  Dorothy T. Thayer,et al.  EM algorithms for ML factor analysis , 1982 .

[68]  S. Boll,et al.  Suppression of acoustic noise in speech using spectral subtraction , 1979 .