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Fundamentals of speech recognition

By:

Rabiner, Lawrence R

Contributor(s):

Juang, B. H

Material type: Text

TextPublication details: Noida Pearson India Education Services Pvt Ltd 2009Description: 497pISBN:

978817585605

Subject(s):

DDC classification:

006.454 RAB

Summary: Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. KEY TOPICS: Covers production, perception, and acoustic-phonetic characterization of the speech signal; signal processing and analysis methods for speech recognition; pattern comparison techniques; speech recognition system design and implementation; theory and implementation of hidden Markov models; speech recognition based on connected word models; large vocabulary continuous speech recognition; and task- oriented application of automatic speech recognition. MARKET: For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Computer science	006.454 RAB (Browse shelf(Opens below))	Available		000992
Book	Plaksha University Library	Computer science	006.454 RAB (Browse shelf(Opens below))	Available		000993

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Previous	006.4 DUD Pattern classification	006.4 JAI Handbook of biometrics	006.454 RAB Fundamentals of speech recognition	006.454 RAB Fundamentals of speech recognition	006.5 QUA Discrete time speech signal processing : principles and practice	006.5 QUA Discrete time speech signal processing : principles and practice	006.6 BEN Object recognition : fundamentals and case studies	Next

Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. KEY TOPICS: Covers production, perception, and acoustic-phonetic characterization of the speech signal; signal processing and analysis methods for speech recognition; pattern comparison techniques; speech recognition system design and implementation; theory and implementation of hidden Markov models; speech recognition based on connected word models; large vocabulary continuous speech recognition; and task- oriented application of automatic speech recognition. MARKET: For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

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