Automatic Speech and Speaker Recognition

[1]  Charles A. Micchelli,et al.  On Spectral Learning , 2010, J. Mach. Learn. Res..

[2]  S. Katagiri,et al.  Discriminative Learning for Minimum Error Classification , 2009 .

[3]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.

[4]  Mark J. F. Gales,et al.  A generalised derivative kernel for speaker verification , 2008, INTERSPEECH.

[5]  Samy Bengio,et al.  A Discriminative Kernel-Based Approach to Rank Images from Text Queries , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Nathan Srebro,et al.  SVM optimization: inverse dependence on training set size , 2008, ICML '08.

[7]  Chih-Jen Lin,et al.  A dual coordinate descent method for large-scale linear SVM , 2008, ICML '08.

[8]  Barbara Caputo,et al.  The projectron: a bounded kernel-based Perceptron , 2008, ICML '08.

[9]  Brian Kingsbury,et al.  Boosted MMI for model and feature-space discriminative training , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[10]  Mehryar Mohri,et al.  Speech Recognition with Weighted Finite-State Transducers , 2008 .

[11]  Yoram Singer,et al.  The Forgetron: A Kernel-Based Perceptron on a Budget , 2008, SIAM J. Comput..

[12]  Francesco Masulli,et al.  A survey of kernel and spectral methods for clustering , 2008, Pattern Recognit..

[13]  Zaïd Harchaoui,et al.  DIFFRAC: a discriminative and flexible framework for clustering , 2007, NIPS.

[14]  Biing-Hwang Juang,et al.  Automatic speech recognition based on weighted minimum classification error (W-MCE) training method , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

[15]  Jinyu Li,et al.  Approximate Test Risk Bound Minimization Through Soft Margin Estimation , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[16]  M.J.F. Gales,et al.  Discriminative Models for Speech Recognition , 2007, 2007 Information Theory and Applications Workshop.

[17]  Samy Bengio,et al.  A kernel trick for sequences applied to text-independent speaker verification systems , 2007, Pattern Recognit..

[18]  Thorsten Brants,et al.  Large Language Models in Machine Translation , 2007, EMNLP.

[19]  Yoram Singer,et al.  Pegasos: primal estimated sub-gradient solver for SVM , 2007, ICML '07.

[20]  Xavier Carreras,et al.  Exponentiated gradient algorithms for log-linear structured prediction , 2007, ICML '07.

[21]  Olivier Chapelle,et al.  Training a Support Vector Machine in the Primal , 2007, Neural Computation.

[22]  Ahmad Emami,et al.  Large-Scale Distributed Language Modeling , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[23]  Hui Jiang,et al.  Incorporating Training Errors for Large Margin HMMS Under Semi-Definite Programming Framework , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[24]  Michael Collins,et al.  Trigger-Based Language Modeling using a Loss-Sensitive Perceptron Algorithm , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[25]  Lawrence K. Saul,et al.  Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[26]  Geoffrey Zweig,et al.  Discriminative Training of Decoding Graphs for Large Vocabulary Continuous Speech Recognition , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[27]  Brian Roark,et al.  Discriminative n-gram language modeling , 2007, Comput. Speech Lang..

[28]  Lawrence K. Saul,et al.  Large margin training of acoustic models for speech recognition , 2007 .

[29]  Georg Heigold,et al.  On the equivalence of Gaussian HMM and Gaussian HMM-like hidden conditional random fields , 2007, INTERSPEECH.

[30]  David Grangier,et al.  A Discriminative Kernel-based Model to Rank Images from Text Queries , 2007 .

[31]  Mark J. F. Gales,et al.  Derivative and parametric kernels for speaker verification , 2007, INTERSPEECH.

[32]  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.

[33]  Lawrence K. Saul,et al.  Large Margin Hidden Markov Models for Automatic Speech Recognition , 2006, NIPS.

[34]  Nello Cristianini,et al.  Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem , 2006, J. Mach. Learn. Res..

[35]  Michael I. Jordan,et al.  Learning Spectral Clustering, With Application To Speech Separation , 2006, J. Mach. Learn. Res..

[36]  Yoram Singer,et al.  Efficient Learning of Label Ranking by Soft Projections onto Polyhedra , 2006, J. Mach. Learn. Res..

[37]  Hui Jiang,et al.  Large margin hidden Markov models for speech recognition , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[38]  Izhak Shafran,et al.  Corrective Models for Speech Recognition of Inflected Languages , 2006, EMNLP.

[39]  Lawrence K. Saul,et al.  Large Margin Gaussian Mixture Modeling for Phonetic Classification and Recognition , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[40]  Douglas E. Sturim,et al.  SVM Based Speaker Verification using a GMM Supervector Kernel and NAP Variability Compensation , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[41]  Mark J. F. Gales,et al.  Augmented Statistical Models for Speech Recognition , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[42]  Frank K. Soong,et al.  A Comparative Study of Discriminative Methods for Reranking LVCSR N-Best Hypotheses in Domain Adaptation and Generalization , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[43]  Douglas E. Sturim,et al.  Support vector machines using GMM supervectors for speaker verification , 2006, IEEE Signal Processing Letters.

[44]  Guy Lebanon,et al.  Metric learning for text documents , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[45]  William M. Campbell,et al.  Support vector machines for speaker and language recognition , 2006, Comput. Speech Lang..

[46]  Brian Roark,et al.  Utterance classification with discriminative language modeling , 2006, Speech Commun..

[47]  Mark J. F. Gales,et al.  Training Augmented Models Using SVMs , 2006, IEICE Trans. Inf. Syst..

[48]  Brian Roark,et al.  MAP adaptation of stochastic grammars , 2006, Comput. Speech Lang..

[49]  Wai Kit Lo,et al.  A multi-pass error detection and correction framework for Mandarin LVCSR , 2006, INTERSPEECH.

[50]  Xiaodong He,et al.  Use of incrementally regulated discriminative margins in MCE training for speech recognition , 2006, INTERSPEECH.

[51]  Samy Bengio,et al.  Posterior based keyword spotting with a priori thresholds , 2006, INTERSPEECH.

[52]  Samy Bengio,et al.  Discriminative kernel-based phoneme sequence recognition , 2006, INTERSPEECH.

[53]  Kilian Q. Weinberger,et al.  Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.

[54]  Jen-Tzung Chien,et al.  Discriminative maximum entropy language model for speech recognition , 2005, INTERSPEECH.

[55]  Berlin Chen,et al.  Minimum word error based discriminative training of language models , 2005, INTERSPEECH.

[56]  Thomas Hofmann,et al.  Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..

[57]  Wei Yuan,et al.  Minimum Sample Risk Methods for Language Modeling , 2005, HLT/EMNLP.

[58]  Alex Acero,et al.  Hidden conditional random fields for phone classification , 2005, INTERSPEECH.

[59]  Brian Roark,et al.  Discriminative Syntactic Language Modeling for Speech Recognition , 2005, ACL.

[60]  Yann LeCun,et al.  Learning a similarity metric discriminatively, with application to face verification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[61]  Patrick Kenny,et al.  Eigenvoice modeling with sparse training data , 2005, IEEE Transactions on Speech and Audio Processing.

[62]  Hui Jiang,et al.  Large margin HMMs for speech recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[63]  Cheng Wu,et al.  Language model estimation for optimizing end-to-end performance of a natural language call routing system , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[64]  Mark J. F. Gales,et al.  Training LVCSR systems on thousands of hours of data , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[65]  Brian Roark,et al.  Joint discriminative language modeling and utterance classification , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[66]  Steve Renals,et al.  Speaker verification using sequence discriminant support vector machines , 2005, IEEE Transactions on Speech and Audio Processing.

[67]  Michael Collins,et al.  Discriminative Reranking for Natural Language Parsing , 2000, CL.

[68]  Jonathan Le Roux,et al.  Optimization methods for discriminative training , 2005, INTERSPEECH.

[69]  François Yvon,et al.  Discriminative training of finite state decoding graphs , 2005, INTERSPEECH.

[70]  Chris H. Q. Ding,et al.  On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering , 2005, SDM.

[71]  Yoram Singer,et al.  The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees , 2004, NIPS.

[72]  Ulrike von Luxburg,et al.  Limits of Spectral Clustering , 2004, NIPS.

[73]  Mehryar Mohri,et al.  Confidence Intervals for the Area Under the ROC Curve , 2004, NIPS.

[74]  William J. Byrne,et al.  Task-specific minimum Bayes-risk decoding using learned edit distance , 2004, INTERSPEECH.

[75]  Mark J. F. Gales,et al.  Maximum margin training of generative kernels , 2004 .

[76]  Brian Roark,et al.  Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm , 2004, ACL.

[77]  Thomas Hofmann,et al.  Support vector machine learning for interdependent and structured output spaces , 2004, ICML.

[78]  Yoram Singer,et al.  An Online Algorithm for Hierarchical Phoneme Classification , 2004, MLMI.

[79]  Brian Roark,et al.  Corrective language modeling for large vocabulary ASR with the perceptron algorithm , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[80]  Brian Roark,et al.  Language Model Adaptation with MAP Estimation and the Perceptron Algorithm , 2004, NAACL.

[81]  Nello Cristianini,et al.  Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..

[82]  Koby Crammer,et al.  On the Learnability and Design of Output Codes for Multiclass Problems , 2002, Machine Learning.

[83]  Claudio Gentile,et al.  On the generalization ability of on-line learning algorithms , 2001, IEEE Transactions on Information Theory.

[84]  Yoram Singer,et al.  BoosTexter: A Boosting-based System for Text Categorization , 2000, Machine Learning.

[85]  Dana Ron,et al.  The power of amnesia: Learning probabilistic automata with variable memory length , 1996, Machine Learning.

[86]  Vaibhava Goel Conditional maximum likelihood estimation for improving annotation performance of n-gram models incorporating stochastic finite state grammars , 2004, INTERSPEECH.

[87]  Jean-Philippe Tarel,et al.  Non-Mercer Kernels for SVM Object Recognition , 2004, BMVC.

[88]  I. Dhillon,et al.  A Unified View of Kernel k-means , Spectral Clustering and Graph Cuts , 2004 .

[89]  William M. Campbell,et al.  Channel compensation for SVM speaker recognition , 2004, Odyssey.

[90]  D. Higham,et al.  A Unified View of Spectral Clustering ∗ , 2004 .

[91]  Samy Bengio,et al.  A statistical significance test for person authentication , 2004, Odyssey.

[92]  Ben Taskar,et al.  Max-Margin Markov Networks , 2003, NIPS.

[93]  Koby Crammer,et al.  Online Passive-Aggressive Algorithms , 2003, J. Mach. Learn. Res..

[94]  Brendan J. Frey,et al.  Probabilistic Inference of Speech Signals from Phaseless Spectrograms , 2003, NIPS.

[95]  Te-Won Lee,et al.  A Maximum Likelihood Approach to Single-channel Source Separation , 2003, J. Mach. Learn. Res..

[96]  Tomer Hertz,et al.  Learning and inferring image segmentations using the GBP typical cut algorithm , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[97]  Jianbo Shi,et al.  Multiclass spectral clustering , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[98]  Shantanu Chakrabartty,et al.  Support vector machines for segmental minimum Bayes risk decoding of continuous speech , 2003, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721).

[99]  Mark J. F. Gales,et al.  Switching linear dynamical systems for speech recognition , 2003 .

[100]  Tomer Hertz,et al.  Learning Distance Functions using Equivalence Relations , 2003, ICML.

[101]  Thomas Hofmann,et al.  Hidden Markov Support Vector Machines , 2003, ICML.

[102]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[103]  W. Press,et al.  Numerical Recipes in C++: The Art of Scientific Computing (2nd edn)1 Numerical Recipes Example Book (C++) (2nd edn)2 Numerical Recipes Multi-Language Code CD ROM with LINUX or UNIX Single-Screen License Revised Version3 , 2003 .

[104]  Gérard Chollet,et al.  Confidence measures for keyword spotting using support vector machines , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[105]  The robustness of an almost-parsing language model given errorful training data , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[106]  Steve Renals,et al.  SVMSVM: support vector machine speaker verification methodology , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[107]  Jeff A. Bilmes,et al.  Buried Markov models: a graphical-modeling approach to automatic speech recognition , 2003, Comput. Speech Lang..

[108]  N. D. Smith,et al.  Using Augmented Statistical Models and Score Spaces for Classification , 2003 .

[109]  Samy Bengio,et al.  The Expected Performance Curve , 2003, ICML 2003.

[110]  Mehryar Mohri,et al.  Weighted automata kernels - general framework and algorithms , 2003, INTERSPEECH.

[111]  J. Beck,et al.  Improving Language Models by Learning from Speech Recognition Errors in a Reading Tutor that Listens , 2003 .

[112]  Roberto Basili,et al.  Learning to Classify Text Using Support Vector Machines: Methods, Theory, and Algorithms by Thorsten Joachims , 2003, Comput. Linguistics.

[113]  Lihao Xu,et al.  Multiway cuts and spec-tral clustering , 2003 .

[114]  Jeff A. Bilmes,et al.  Graphical models and automatic speech recognition , 2002 .

[115]  Simon King,et al.  Framewise phone classification using support vector machines , 2002, INTERSPEECH.

[116]  Thorsten Joachims,et al.  Optimizing search engines using clickthrough data , 2002, KDD.

[117]  Michael Collins,et al.  Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms , 2002, EMNLP.

[118]  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.

[119]  Chin-Hui Lee,et al.  Discriminative training of language models for speech recognition , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[120]  William M. Campbell,et al.  Generalized linear discriminant sequence kernels for speaker recognition , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[121]  Daniel Povey,et al.  Large scale discriminative training of hidden Markov models for speech recognition , 2002, Comput. Speech Lang..

[122]  John Shawe-Taylor,et al.  String Kernels, Fisher Kernels and Finite State Automata , 2002, NIPS.

[123]  Thomas Hofmann,et al.  Discriminative Learning for Label Sequences via Boosting , 2002, NIPS.

[124]  Dustin Boswell,et al.  Introduction to Support Vector Machines , 2002 .

[125]  Michael I. Jordan,et al.  Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.

[126]  Fernando Pereira,et al.  Weighted finite-state transducers in speech recognition , 2002, Comput. Speech Lang..

[127]  Samy Bengio,et al.  Torch: a modular machine learning software library , 2002 .

[128]  Koby Crammer,et al.  On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..

[129]  Jitendra Malik,et al.  Efficient spatiotemporal grouping using the Nystrom method , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[130]  Joshua Goodman,et al.  A bit of progress in language modeling , 2001, Comput. Speech Lang..

[131]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[132]  Eugene Charniak,et al.  Immediate-Head Parsing for Language Models , 2001, ACL.

[133]  Claire Cardie,et al.  Proceedings of the Eighteenth International Conference on Machine Learning, 2001, p. 577–584. Constrained K-means Clustering with Background Knowledge , 2022 .

[134]  Andrew McCallum,et al.  Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.

[135]  Brian Roark,et al.  Probabilistic Top-Down Parsing and Language Modeling , 2001, CL.

[136]  Mukund Padmanabhan,et al.  Error corrective mechanisms for speech recognition , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[137]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[138]  Nello Cristianini,et al.  Spectral Kernel Methods for Clustering , 2001, NIPS.

[139]  Tommi S. Jaakkola,et al.  Partially labeled classification with Markov random walks , 2001, NIPS.

[140]  Mark J. F. Gales,et al.  Speech Recognition using SVMs , 2001, NIPS.

[141]  Barak A. Pearlmutter,et al.  Blind Source Separation via Multinode Sparse Representation , 2001, NIPS.

[142]  Jianbo Shi,et al.  Grouping with Bias , 2001, NIPS.

[143]  Chris H. Q. Ding,et al.  Spectral Relaxation for K-means Clustering , 2001, NIPS.

[144]  H. V. Trees Detection, Estimation, And Modulation Theory , 2001 .

[145]  C. Ding,et al.  Spectral relaxation models and structure analysis for K-way graph clustering and bi-clustering , 2001 .

[146]  Harriet J. Nock,et al.  Techniques for modelling Phonological Processes in Automatic Speech Recognition , 2001 .

[147]  Ronald Rosenfeld,et al.  Whole-sentence exponential language models: a vehicle for linguistic-statistical integration , 2001, Comput. Speech Lang..

[148]  Frederick Jelinek,et al.  Structured language modeling , 2000, Comput. Speech Lang..

[149]  Mingjing Li,et al.  Discriminative training on language model , 2000, INTERSPEECH.

[150]  Jun Wu,et al.  Maximum entropy techniques for exploiting syntactic, semantic and collocational dependencies in language modeling , 2000, Comput. Speech Lang..

[151]  Andreas Stolcke,et al.  Finding consensus in speech recognition: word error minimization and other applications of confusion networks , 2000, Comput. Speech Lang..

[152]  Özgür Yilmaz,et al.  Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[153]  Vaibhava Goel,et al.  Minimum Bayes-risk automatic speech recognition , 2000, Comput. Speech Lang..

[154]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[155]  Ralf Herbrich,et al.  Large margin rank boundaries for ordinal regression , 2000 .

[156]  Sam T. Roweis,et al.  One Microphone Source Separation , 2000, NIPS.

[157]  Andreas Stolcke,et al.  THE SRI MARCH 2000 HUB-5 CONVERSATIONAL SPEECH TRANSCRIPTION SYSTEM , 2000 .

[158]  H. Sebastian Seung,et al.  Algorithms for Non-negative Matrix Factorization , 2000, NIPS.

[159]  Roni Rosenfeld,et al.  Minimum Classification Error Training in Exponential Language Models , 2000 .

[160]  Jianbo Shi,et al.  Learning Segmentation by Random Walks , 2000, NIPS.

[161]  Douglas A. Reynolds,et al.  Speaker Verification Using Adapted Gaussian Mixture Models , 2000, Digit. Signal Process..

[162]  Andrew W. Moore,et al.  'N-Body' Problems in Statistical Learning , 2000, NIPS.

[163]  I. Lee Hetherington,et al.  Keyword-based discriminative training of acoustic models , 2000, INTERSPEECH.

[164]  Naftali Tishby,et al.  Data Clustering by Markovian Relaxation and the Information Bottleneck Method , 2000, NIPS.

[165]  Yair Weiss,et al.  Segmentation using eigenvectors: a unifying view , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[166]  David R. Musicant,et al.  Successive overrelaxation for support vector machines , 1999, IEEE Trans. Neural Networks.

[167]  John C. Platt,et al.  Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .

[168]  Stanley F. Chen,et al.  A Gaussian Prior for Smoothing Maximum Entropy Models , 1999 .

[169]  Daniel P. W. Ellis,et al.  Speech and Audio Signal Processing - Processing and Perception of Speech and Music, Second Edition , 1999 .

[170]  Andreas Stolcke,et al.  Finding consensus among words: lattice-based word error minimization , 1999, EUROSPEECH.

[171]  Hervé Bourlard,et al.  Iterative Posterior-Based Keyword Spotting Without Filler Models , 1999 .

[172]  Thorsten Joachims,et al.  Making large-scale support vector machine learning practical , 1999 .

[173]  David Haussler,et al.  Exploiting Generative Models in Discriminative Classifiers , 1998, NIPS.

[174]  Frédéric Bimbot,et al.  A comparative evaluation of variance flooring techniques in HMM-based speaker verification , 1998, ICSLP.

[175]  Yoav Freund,et al.  Large Margin Classification Using the Perceptron Algorithm , 1998, COLT' 98.

[176]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[177]  Yoav Freund,et al.  Self bounding learning algorithms , 1998, COLT' 98.

[178]  Marina Meila,et al.  An Experimental Comparison of Several Clustering and Initialization Methods , 1998, UAI.

[179]  Alan Edelman,et al.  The Geometry of Algorithms with Orthogonality Constraints , 1998, SIAM J. Matrix Anal. Appl..

[180]  J. C. BurgesChristopher A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .

[181]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[182]  S. Mallat A wavelet tour of signal processing , 1998 .

[183]  Jeff A. Bilmes,et al.  A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .

[184]  Alvin F. Martin,et al.  The DET curve in assessment of detection task performance , 1997, EUROSPEECH.

[185]  Harald Höge,et al.  Efficient methods for detecting keywords in continuous speech , 1997, EUROSPEECH.

[186]  Mehryar Mohri,et al.  Weighted determinization and minimization for large vocabulary speech recognition , 1997, EUROSPEECH.

[187]  Steve J. Young,et al.  MMIE training of large vocabulary recognition systems , 1997, Speech Communication.

[188]  Yoav Freund,et al.  Boosting the margin: A new explanation for the effectiveness of voting methods , 1997, ICML.

[189]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[190]  Biing-Hwang Juang,et al.  Minimum classification error rate methods for speech recognition , 1997, IEEE Trans. Speech Audio Process..

[191]  Mitch Weintraub,et al.  Neural-network based measures of confidence for word recognition , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[192]  E. Domany,et al.  Data Clustering Using a Model Granular Magnet , 1997, Neural Computation.

[193]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.

[194]  Thomas Niesler,et al.  Combination of word-based and category-based language models , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[195]  Steve Young,et al.  A review of large-vocabulary continuous-speech recognition , 1996 .

[196]  Mari Ostendorf,et al.  From HMM's to segment models: a unified view of stochastic modeling for speech recognition , 1996, IEEE Trans. Speech Audio Process..

[197]  Chin-Hui Lee,et al.  Utterance verification of keyword strings using word-based minimum verification error (WB-MVE) training , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[198]  Eric K. Ringger,et al.  Error correction via a post-processor for continuous speech recognition , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[199]  Thomas Niesler,et al.  A variable-length category-based n-gram language model , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[200]  Rakesh Dugad,et al.  A Tutorial On Hidden Markov Models , 1996 .

[201]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[202]  Yoram Singer,et al.  Beyond Word N-Grams , 1996, VLC@ACL.

[203]  Mitchel Weintraub,et al.  LVCSR log-likelihood ratio scoring for keyword spotting , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[204]  Vladimir Naumovich Vapni The Nature of Statistical Learning Theory , 1995 .

[205]  Guy J. Brown,et al.  Computational auditory scene analysis , 1994, Comput. Speech Lang..

[206]  Chin-Hui Lee,et al.  Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains , 1994, IEEE Trans. Speech Audio Process..

[207]  Anthony J. Robinson,et al.  An application of recurrent nets to phone probability estimation , 1994, IEEE Trans. Neural Networks.

[208]  Michael L. Overton,et al.  Optimality conditions and duality theory for minimizing sums of the largest eigenvalues of symmetric matrices , 2015, Math. Program..

[209]  Hervé Bourlard,et al.  Connectionist Speech Recognition: A Hybrid Approach , 1993 .

[210]  Martine D. F. Schlag,et al.  Spectral K-Way Ratio-Cut Partitioning and Clustering , 1993, 30th ACM/IEEE Design Automation Conference.

[211]  Michael Weintraub,et al.  Keyword-spotting using SRI's DECIPHER large-vocabulary speech-recognition system , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[212]  Steve J. Young,et al.  MMI training for continuous phoneme recognition on the TIMIT database , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[213]  Ronald Rosenfeld,et al.  Trigger-based language models: a maximum entropy approach , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[214]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[215]  Lalit R. Bahl,et al.  Estimating hidden Markov model parameters so as to maximize speech recognition accuracy , 1993, IEEE Trans. Speech Audio Process..

[216]  Biing-Hwang Juang,et al.  Discriminative learning for minimum error classification [pattern recognition] , 1992, IEEE Trans. Signal Process..

[217]  Robert L. Mercer,et al.  Class-Based n-gram Models of Natural Language , 1992, CL.

[218]  Philip C. Woodland,et al.  Hidden Markov models using vector linear prediction and discriminative output distributions , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[219]  Janet M. Baker,et al.  The Design for the Wall Street Journal-based CSR Corpus , 1992, HLT.

[220]  P. Tseng,et al.  On the convergence of the coordinate descent method for convex differentiable minimization , 1992 .

[221]  Vassilios Digalakis,et al.  Segment-based stochastic models of spectral dynamics for continuous speech recognition , 1992 .

[222]  Dimitri Kanevsky,et al.  An inequality for rational functions with applications to some statistical estimation problems , 1991, IEEE Trans. Inf. Theory.

[223]  Chin-Hui Lee,et al.  Automatic recognition of keywords in unconstrained speech using hidden Markov models , 1990, IEEE Trans. Acoust. Speech Signal Process..

[224]  G. Golub,et al.  Tracking a few extreme singular values and vectors in signal processing , 1990, Proc. IEEE.

[225]  Richard Rose,et al.  A hidden Markov model based keyword recognition system , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[226]  Guy L. Scott,et al.  Feature grouping by 'relocalisation' of eigenvectors of the proximity matrix , 1990, BMVC.

[227]  Hsiao-Wuen Hon,et al.  Speaker-independent phone recognition using hidden Markov models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[228]  Toshiyuki Hanazawa,et al.  Word spotting method based on HMM phoneme recognition , 1988 .

[229]  Hsiao-Wuen Hon,et al.  Large-vocabulary speaker-independent continuous speech recognition using HMM , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[230]  C. J. Wellekens,et al.  Explicit time correlation in hidden Markov models for speech recognition , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[231]  Lalit R. Bahl,et al.  Maximum mutual information estimation of hidden Markov model parameters for speech recognition , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[232]  Sadaoki Furui,et al.  Speaker-independent isolated word recognition using dynamic features of speech spectrum , 1986, IEEE Trans. Acoust. Speech Signal Process..

[233]  R. Wohlford,et al.  Keyword recognition using template concatenation , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[234]  A. Nadas,et al.  A decision theorectic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood , 1983 .

[235]  Jae S. Lim,et al.  Signal estimation from modified short-time Fourier transform , 1983, ICASSP.

[236]  Sahibsingh A. Dudani The Distance-Weighted k-Nearest-Neighbor Rule , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[237]  Edward L. Wilson,et al.  Numerical methods in finite element analysis , 1976 .

[238]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[239]  G. Wahba,et al.  Some results on Tchebycheffian spline functions , 1971 .

[240]  Clifford Hildreth,et al.  A quadratic programming procedure , 1957 .

[241]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[242]  F. Wilcoxon Individual Comparisons by Ranking Methods , 1945 .

[243]  I. Song,et al.  Working Set Selection Using Second Order Information for Training Svm, " Complexity-reduced Scheme for Feature Extraction with Linear Discriminant Analysis , 2022 .