INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
0130151572
NATIONAL BIBLIOGRAPHY NUMBER
Country Code
IR
Number
EN-56657
LANGUAGE OF THE ITEM
.Language of Text, Soundtrack etc
انگلیسی
COUNTRY OF PUBLICATION OR PRODUCTlON
Country of publication
IR
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Fundamentals of speech recognition
General Material Designation
[Book]
First Statement of Responsibility
/ Lawrence Rabiner, Biing-Hwang Juang
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Englewood Cliffs, N.J.
Name of Publisher, Distributor, etc.
: PTR Prentice Hall,
Date of Publication, Distribution, etc.
, c1993.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xxxv, 507 p. , ill. , 25 cm.
SERIES
Series Title
(Prentice Hall signal processing series)
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Electronic
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
8.5. Language Models for Large Vocabulary Speech Recognition. 8.6. Statistical Language Modeling. 8.7. Perplexity of the Language Model. 8.8. Overall Recognition System Based on Subword Units. 8.9. Context-Dependent Subword Units. 8.10. Creation of Vocabulary-Independent Units. 8.11. Semantic Postprocessor for Recognition -- 9. Task Oriented Applications of Automatic Speech Recognition. 9.2. Speech-Recognizer Performance Scores. 9.3. Characteristics of Speech-Recognition Applications. 9.4. Broad Classes of Speech-Recognition Applications. 9.5. Command-and-Control Applications. 9.6. Projections for Speech Recognition.
Text of Note
7. Speech Recognition Based on Connected Word Models. 7.2. General Notation for the Connected Word-Recognition Problem. 7.3. The Two-Level Dynamic Programming (Two-Level DP) Algorithm. 7.4. The Level Building (LB) Algorithm. 7.5. The One-Pass (One-State) Algorithm. 7.6. Multiple Candidate Strings. 7.7. Summary of Connected Word Recognition Algorithms. 7.8. Grammar Networks for Connected Digit Recognition. 7.9. Segmental K-Means Training Procedure. 7.10. Connected Digit Recognition Implementation -- 8. Large Vocabulary Continuous Speech Recognition. 8.2. Subword Speech Units. 8.3. Subword Unit Models Based on HMMs. 8.4. Training of Subword Units.
Text of Note
6. Theory and Implementation of Hidden Markov Models. 6.2. Discrete-Time Markov Processes. 6.3. Extensions to Hidden Markov Models. 6.4. The Three Basic Problems for HMMs. 6.5. Types of HMMs. 6.6. Continuous Observation Densities in HMMs. 6.7. Autoregressive HMMs. 6.8. Variants on HMM Structures - Null Transitions and Tied States. 6.9. Inclusion of Explicit State Duration Density in HMMs. 6.10. Optimization Criterion - ML, MMI, and MDI. 6.11. Comparisons of HMMs. 6.12. Implementation Issues for HMMs. 6.13. Improving the Effectiveness of Model Estimates. 6.14. Model Clustering and Splitting. 6.15. HMM System for Isolated Word Recognition --
Text of Note
4. Pattern-Comparison Techniques. 4.2. Speech (Endpoint) Detection. 4.3. Distortion Measures - Mathematical Considerations. 4.4. Distortion Measures - Perceptual Considerations. 4.5. Spectral-Distortion Measures. 4.6. Incorporation of Spectral Dynamic Features into the Distortion Measure. 4.7. Time Alignment and Normalization -- 5. Speech Recognition System Design and Implementation Issues. 5.2. Application of Source-Coding Techniques to Recognition. 5.3. Template Training Methods. 5.4. Performance Analysis and Recognition Enhancements. 5.5. Template Adaptation to New Talkers. 5.6. Discriminative Methods in Speech Recognition. 5.7. Speech Recognition in Adverse Environments --
Text of Note
1. Fundamentals of Speech Recognition. 1.2. The Paradigm for Speech Recognition. 1.3. Outline. 1.4. A Brief History of Speech-Recognition Research -- 2. The Speech Signal: Production, Perception, and Acoustic-Phonetic Characterization. 2.2. The Speech-Production Process. 2.3. Representing Speech in the Time and Frequency Domains. 2.4. Speech Sounds and Features. 2.5. Approaches to Automatic Speech Recognition by Machine -- 3. Signal Processing and Analysis Methods for Speech Recognition. 3.2. The Bank-of-Filters Front-End Processor. 3.3. Linear Predictive Coding Model for Speech Recognition. 3.4. Vector Quantization. 3.5. Auditory-Based Spectral Analysis Models --
SERIES
Title
Prentice-Hall signal processing series
TOPICAL NAME USED AS SUBJECT
Automatic speech recognition
Speech processing systems
LIBRARY OF CONGRESS CLASSIFICATION
Class number
E-BOOK
PERSONAL NAME - PRIMARY RESPONSIBILITY
Rabiner, Lawrence R., 1943-
PERSONAL NAME - SECONDARY RESPONSIBILITY
Juang, B. H. (Biing-Hwang)
ORIGINATING SOURCE
Country
ایران
ELECTRONIC LOCATION AND ACCESS
Host name
0130151572.pdf
Access number
عادی
Compression information
عادی
Date and Hour of Consultation and Access
0130151572.pdf
Electronic Format Type
متن
old catalog
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