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Pattern Recognition in Speech and Language Processing

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acoustic
Acoustic Models
adaptive
advanced pattern recognition systems
ASR
ASR System
Bayes Decision Rule
Bayes Decision Theory
Category=UYQ
Category=UYU
classifier optimization
computational linguistics
conditional
CRC Press LLC
decision
Discriminant Functions
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Feature Vectors
HMM Parameter
HMMs
huo
Language Model
Loss Function
LSA Space
minimax
Misclassification Measure
model
Model IBM
neural network models
Posterior PDF
qiang
rule
rules
Semantic Information
semantic knowledge extraction
Speaker Verification
Speech Recognition
Speech Recognizer
spontaneous speech analysis
statistical modeling techniques
Training Data
Training Sample Set
Utterance Verification
WER
Word String

Product details

  • ISBN 9780849312328
  • Weight: 930g
  • Dimensions: 156 x 234mm
  • Publication Date: 26 Feb 2003
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description
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.