Optimization Algorithms and Applications for Speech and Language Processing
暂无分享,去创建一个
Haizhou Li | Stephen J. Wright | Georg Heigold | Li Deng | Dimitri Kanevsky | Xiaodong He | Xiaodong He | L. Deng | D. Kanevsky | G. Heigold | Haizhou Li
[1] Yehoshua Bar-Hillel,et al. The Present Status of Automatic Translation of Languages , 1960, Adv. Comput..
[2] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[3] J. Darroch,et al. Generalized Iterative Scaling for Log-Linear Models , 1972 .
[4] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[5] New York Dover,et al. ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .
[6] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[7] Dimitri Kanevsky,et al. An inequality for rational functions with applications to some statistical estimation problems , 1991, IEEE Trans. Inf. Theory.
[8] Salvatore D. Morgera,et al. An improved MMIE training algorithm for speaker-independent, small vocabulary, continuous speech recognition , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.
[9] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.
[10] Robert L. Mercer,et al. The Mathematics of Statistical Machine Translation: Parameter Estimation , 1993, CL.
[11] Renato De Mori,et al. High-performance connected digit recognition using maximum mutual information estimation , 1994, IEEE Trans. Speech Audio Process..
[12] Philip C. Woodland,et al. Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models , 1995, Comput. Speech Lang..
[13] O. Nelles,et al. An Introduction to Optimization , 1996, IEEE Antennas and Propagation Magazine.
[14] John D. Lafferty,et al. Inducing Features of Random Fields , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[15] Biing-Hwang Juang,et al. Minimum classification error rate methods for speech recognition , 1997, IEEE Trans. Speech Audio Process..
[16] Stanley F. Chen,et al. A Gaussian Prior for Smoothing Maximum Entropy Models , 1999 .
[17] EntropyModelsStanley,et al. A Gaussian Prior for Smoothing Maximum , 1999 .
[18] Qiang Huo,et al. On adaptive decision rules and decision parameter adaptation for automatic speech recognition , 2000, Proceedings of the IEEE.
[19] Alex Pentland,et al. On Reversing Jensen's Inequality , 2000, NIPS.
[20] Douglas A. Reynolds,et al. Speaker Verification Using Adapted Gaussian Mixture Models , 2000, Digit. Signal Process..
[21] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.
[22] Hermann Ney,et al. Comparison of discriminative training criteria and optimization methods for speech recognition , 2001, Speech Commun..
[23] D K Smith,et al. Numerical Optimization , 2001, J. Oper. Res. Soc..
[24] Daniel Povey,et al. Minimum Phone Error and I-smoothing for improved discriminative training , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[25] Daniel Povey,et al. Large scale discriminative training of hidden Markov models for speech recognition , 2002, Comput. Speech Lang..
[26] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[27] Hermann Ney,et al. A comparative study on maximum entropy and discriminative training for acoustic modeling in automatic speech recognition , 2003, INTERSPEECH.
[28] Franz Josef Och,et al. Minimum Error Rate Training in Statistical Machine Translation , 2003, ACL.
[29] Alvin F. Martin,et al. NIST 2003 language recognition evaluation , 2003, INTERSPEECH.
[30] Daniel Marcu,et al. Statistical Phrase-Based Translation , 2003, NAACL.
[31] Thomas P. Minka,et al. Algorithms for maximum-likelihood logistic regression , 2003 .
[32] Niko Brümmer,et al. Application-independent evaluation of speaker detection , 2006, Comput. Speech Lang..
[33] Dimitri Kanevsky. Extended Baum transformations for general functions , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[34] D. Kanevsky. Extended Baum Transformations for General Functions , II , 2005 .
[35] Mohamed Afify. Extended baum-welch reestimation of Gaussian mixture models based on reverse Jensen inequality , 2005, INTERSPEECH.
[36] Alex Acero,et al. Hidden conditional random fields for phone classification , 2005, INTERSPEECH.
[37] William M. Campbell,et al. Support vector machines for speaker and language recognition , 2006, Comput. Speech Lang..
[38] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[39] N. Brummer,et al. On calibration of language recognition scores , 2006, 2006 IEEE Odyssey - The Speaker and Language Recognition Workshop.
[40] Alvin F. Martin,et al. The Current State of Language Recognition: NIST 2005 Evaluation Results , 2006, 2006 IEEE Odyssey - The Speaker and Language Recognition Workshop.
[41] Scott Axelrod,et al. Discriminative Estimation of Subspace Constrained Gaussian Mixture Models for Speech Recognition , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[42] Bin Ma,et al. A Vector Space Modeling Approach to Spoken Language Identification , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[43] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[44] John S. Garofolo,et al. NIST Speech Processing Evaluations: LVCSR, Speaker Recognition, Language Recognition , 2007 .
[45] 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.
[46] Frank K. Soong,et al. A Constrained Line Search Optimization for Discriminative Training in Speech Recognition , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[47] Wiebe van der Hoek,et al. SOFSEM 2007: Theory and Practice of Computer Science , 2007 .
[48] David A. van Leeuwen,et al. An Introduction to Application-Independent Evaluation of Speaker Recognition Systems , 2007, Speaker Classification.
[49] Haizhou Li,et al. Vector-Based Spoken Language Classification , 2008 .
[50] Bin Ma,et al. Optimizing the Performance of Spoken Language Recognition With Discriminative Training , 2008, IEEE Transactions on Audio, Speech, and Language Processing.
[51] Zhi-Quan Luo,et al. A convex optimization method for joint mean and variance parameter estimation of large-margin CDHMM , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[52] Brian Kingsbury,et al. Boosted MMI for model and feature-space discriminative training , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[53] Georg Heigold,et al. A GIS-like training algorithm for log-linear models with hidden variables , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[54] Wu Chou,et al. Discriminative learning in sequential pattern recognition , 2008, IEEE Signal Processing Magazine.
[55] Tara N. Sainath,et al. Generalization of extended baum-welch parameter estimation for discriminative training and decoding , 2008, INTERSPEECH.
[56] Patrick Kenny,et al. A Study of Interspeaker Variability in Speaker Verification , 2008, IEEE Transactions on Audio, Speech, and Language Processing.
[57] Niko Brümmer,et al. Measuring, refining and calibrating speaker and language information extracted from speech , 2010 .
[58] Tara N. Sainath,et al. Sparse representation features for speech recognition , 2010, INTERSPEECH.
[59] Haizhou Li,et al. TechWare: Speaker and Spoken Language Recognition Resources , 2010 .
[60] Haizhou Li,et al. An overview of text-independent speaker recognition: From features to supervectors , 2010, Speech Commun..
[61] Thomas Hain,et al. Error Approximation and Minimum Phone Error Acoustic Model Estimation , 2010, IEEE Transactions on Audio, Speech, and Language Processing.
[62] Li Deng,et al. A Geometric Perspective of Large-Margin Training of Gaussian Models [Lecture Notes] , 2010, IEEE Signal Processing Magazine.
[63] Bin Ma,et al. TechWare: Speaker and Spoken Language Recognition Resources [Best of the Web] , 2010, IEEE Signal Processing Magazine.
[64] Kemal Oflazer,et al. Exploiting Morphology and Local Word Reordering in English-to-Turkish Phrase-Based Statistical Machine Translation , 2010, IEEE Transactions on Audio, Speech, and Language Processing.
[65] Georg Heigold,et al. A log-linear discriminative modeling framework for speech recognition , 2010 .
[66] Haizhou Li,et al. A Maximum-Entropy Segmentation Model for Statistical Machine Translation , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[67] Patrick Kenny,et al. Front-End Factor Analysis for Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[68] T. Kinnunen,et al. Using Discrete Probabilities With Bhattacharyya Measure for SVM-Based Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[69] Georg Heigold,et al. EM-style optimization of hidden conditional random fields for grapheme-to-phoneme conversion , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[70] Yu Hu,et al. Trust Region-Based Optimization for Maximum Mutual Information Estimation of HMMs in Speech Recognition , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[71] Tanja Schultz,et al. Generalized Baum-Welch Algorithm and its Implication to a New Extended Baum-Welch Algorithm , 2011, INTERSPEECH.
[72] Dong Yu,et al. Deep Convex Net: A Scalable Architecture for Speech Pattern Classification , 2011, INTERSPEECH.
[73] Li Deng,et al. Speech Recognition, Machine Translation, and Speech Translation—A Unified Discriminative Learning Paradigm [Lecture Notes] , 2011, IEEE Signal Processing Magazine.
[74] Lirong Dai,et al. Trust Region-Based Optimization for Maximum Mutual Information Estimation of HMMs in Speech Recognition , 2011 .
[75] Tara N. Sainath,et al. A-Functions: A generalization of Extended Baum-Welch transformations to convex optimization , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[76] Geoffrey E. Hinton,et al. Generating Text with Recurrent Neural Networks , 2011, ICML.
[77] Georg Heigold,et al. Equivalence of Generative and Log-Linear Models , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[78] Li Deng,et al. Maximum Expected BLEU Training of Phrase and Lexicon Translation Models , 2012, ACL.
[79] Shinji Watanabe,et al. Bayesian approaches to acoustic modeling: a review , 2012, APSIPA Transactions on Signal and Information Processing.
[80] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[81] Tara N. Sainath,et al. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups , 2012, IEEE Signal Processing Magazine.
[82] Dong Yu,et al. Scalable stacking and learning for building deep architectures , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[83] 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.
[84] Nelson Morgan,et al. Deep and Wide: Multiple Layers in Automatic Speech Recognition , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[85] Jen-Tzung Chien,et al. Bayesian Sensing Hidden Markov Models , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[86] Tara N. Sainath,et al. Scalable Minimum Bayes Risk Training of Deep Neural Network Acoustic Models Using Distributed Hessian-free Optimization , 2012, INTERSPEECH.
[87] Geoffrey E. Hinton,et al. Acoustic Modeling Using Deep Belief Networks , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[88] Tara N. Sainath,et al. Deep Neural Networks for Acoustic Modeling in Speech Recognition , 2012 .
[89] Bin Ma,et al. Sparse Classifier Fusion for Speaker Verification , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[90] Dong Yu,et al. Tensor Deep Stacking Networks , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[91] Tara N. Sainath,et al. Optimization Techniques to Improve Training Speed of Deep Neural Networks for Large Speech Tasks , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[92] Chin-Hui Lee,et al. Exploiting deep neural networks for detection-based speech recognition , 2013, Neurocomputing.
[93] Li Deng,et al. Speech-Centric Information Processing: An Optimization-Oriented Approach , 2013, Proceedings of the IEEE.
[94] Xiao Li,et al. Machine Learning Paradigms for Speech Recognition: An Overview , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[95] Brian Kingsbury,et al. New types of deep neural network learning for speech recognition and related applications: an overview , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[96] Bin Ma,et al. Spoken Language Recognition: From Fundamentals to Practice , 2013, Proceedings of the IEEE.