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Spoken Language Processing A Guide to Theory, Algorithm and System Development

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ISBN-10: 0130226165

ISBN-13: 9780130226167

Edition: 2001

Authors: Xuedong Huang, Alex Acero, Hsiao-Wuen Hon

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This will be the definitive book on spoken language systems written by the people at Microsoft Research who have developed the voic-activated technologies that will be imbedded in Windows 2000 and other key Microsoft products of the future. This is not a Microsoft book, however, this is a book on the science and linguistics of this technology and how to use it in developing and building hardware and software products.
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Book details

Copyright year: 2001
Publisher: Prentice Hall PTR
Publication date: 4/25/2001
Binding: Paperback
Pages: 1008
Size: 7.25" wide x 9.25" long x 1.75" tall
Weight: 3.520
Language: English

Spoken Language System Architecture
Book Organization
Target Audiences
Spoken language Structure
Sound and Human Speech Systems
Phonetics and Phonology
Syllables and Words
Syntax and Semantics
Probability, Statistics, and Information Theory
Probability Theory
Estimation Theory
Significance Testing
Information Theory
Pattern Recognition
Bayes' Decision Theory
How to Construct Classifiers
Discriminative Training
Unsupervised Estimation Methods
Classification and Regression Trees
Speech Processing
Digital Signal Processing
Digital Signals and Systems
Continuous-Frequency Transforms
Discrete-Frequency Transforms
Digital Filters and Windows
Digital Processing of Analog Signals
Multirate Signal Processing
Stochastic Processes
Speech Signal Representations
Short-Time Fourier Analysis
Acoustical Model of Speech Production
Linear Predictive Coding
Cepstral Processing
Perceptually Motivated Representations
Formant Frequencies
The Role of Pitch
Speech Coding
Speech Coders Attributes
Scalar Waveform Coders
Scalar Frequency Domain Coders
Code Excited Linear Prediction (CELP)
Low-Brit Speech Coders
Hidden Markov Models
The Markov Chain
Definition of the Hidden Markov Model
Continuous and Semicontinuous HMMs
Practical Issues in Using HMMs
HMM Limitations
Acoustic Modeling
Variability in the Speech Signal
How to Measure Speech Recognition Errors
Signal Processing-Extracting Features
Phonectic Modeling-Selecting Appropriate Units
Acoustic Modeling-Scoring Acoustic Features
Adaptive Techniques-Minimizing Mismatches
Confidence Measures: Measuring the Reliability
Other Techniques
Case Study: Whisper
Environmental Robustness
The Acoustical Environment
Acoustical Transducers
Adaptive Echo Cancellation (AEC)
Multimicrophone Speech Enhancement
Environment Compensation Preprocessing
Environment Model Adaptation
Modeling Nonstationary Noise
Language Modeling
Formal Language Theory
Stochastic Language Models
Complexity Measure of Language Models
N-Gram Smoothing
Adaptive Language Models
Practical Issues
Basic Search Algorithms
Basic Search Algorithms
Search Algorithms for Speech Recognition
Language Model States
Time-Synchronous Viterbi Beam Search
Stack Decoding (A Search)
Large-Vocabulary Search Algorithms
Efficient Manipulation of a Tree Lexicon
Other Efficient Search Techniques
N-Best and Multipass Search Strategies
Search-Algorithm Evaluation
Case Study-Microsoft Whisper
Text and Phonetic Analysis
Modules and Data Flow
Document Structured Detection
Text Normalization
Linguistic Analysis
Homograph Disambiguation
Morphological Analysis