Pattern Recognition in Speech and Language Processing (Google eBook)
Wu Chou, Biing-Hwang Juang
CRC Press, Feb 26, 2003 - Technology & Engineering - 416 pages
Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field.
Pattern Recognition in Speech and Language Processing offers a systematic, up-to-date presentation of these recent developments. It begins with the fundamentals and recent theoretical advances in pattern recognition, with emphasis on classifier design criteria and optimization procedures. The focus then shifts to the application of these techniques to speech processing, with chapters exploring advances in applying pattern recognition to real speech and audio processing systems. The final section of the book examines topics related to pattern recognition in language processing: topics that represent promising new trends with direct impact on information processing systems for the Web, broadcast news, and other content-rich information resources.
Each self-contained chapter includes figures, tables, diagrams, and references. The collective effort of experts at the forefront of the field, Pattern Recognition in Speech and Language Processing offers in-depth, insightful discussions on new developments and contains a wealth of information integral to the further development of human-machine communications.
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2 Minimum BayesRisk Methods in Automatic Speech Recognition
3 A Decision Theoretic Formulation for Robust Automatic Speech Recognition
4 Speech Pattern Recognition using Neural Networks
5 Large Vocabulary Speech Recognition Based on Statistical Methods
6 Toward Spontaneous Speech Recognition and Understanding
7 Speaker Authentication
8 HMMs for Language Processing Problems
9 Statistical Language Models With Embedded Latent Semantic Knowledge
10 Semantic Information Processing of Spoken LanguageHow May I Help You?sm
11 Machine Translation Using Statistical Modeling
12 Modeling Topics for Detection and Tracking
Other editions - View all
acoustic models adaptation algorithm applications Audio Processing automatic speech recognition Bayesian bigram cepstral classifier design clustering combined string model Computer Conf context continuous speech recognition corpus corresponding decision rule decoding dependent discriminative training distribution document estimation evaluation example feature vector Figure H.Ney hidden Markov models hypothesis IEEE IEEE Trans input language model large vocabulary lattice Levenshtein distance linguistic loss function LVCSR maximum likelihood MCE approach method minimization minimum classification error misclassification measure model parameters N-best list n-gram optimal pattern recognition performance posterior probability probabilistic problem Proc procedure recognizer robust segmentation semantic sentence Signal Processing space speaker recognition speaker verification speech signal Spoken Language spontaneous speech statistical stories subword summarization target task techniques topic training data training sample transcription translation utterance verification word error rate word sequence word string Workshop