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Speech Recognition

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Speech & Language Processing

Speech & Language Processing
Author :
Publisher : Pearson Education India
Total Pages : 912
Release :
ISBN-10 : 8131716724
ISBN-13 : 9788131716724
Rating : 4/5 (24 Downloads)
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Book Synopsis Speech & Language Processing by : Dan Jurafsky

Download or read book Speech & Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Speech & Language Processing Related Books

Speech & Language Processing
Language: en
Pages: 912

Speech & Language Processing

Authors: Dan Jurafsky
Categories:
Type: BOOK - Published: 2000-09 - Publisher: Pearson Education India

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Automatic Speech Recognition
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Automatic Speech Recognition

Authors: Dong Yu
Categories: Technology & Engineering
Type: BOOK - Published: 2014-11-11 - Publisher: Springer

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This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models includin
Statistical Methods for Speech Recognition
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Statistical Methods for Speech Recognition

Authors: Frederick Jelinek
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2022-11-01 - Publisher: MIT Press

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This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as
Advances in Speech Recognition
Language: en
Pages: 383

Advances in Speech Recognition

Authors: Amy Neustein
Categories: Technology & Engineering
Type: BOOK - Published: 2010-09-21 - Publisher: Springer Science & Business Media

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Two Top Industry Leaders Speak Out Judith Markowitz When Amy asked me to co-author the foreword to her new book on advances in speech recognition, I was honored
Deep Learning for NLP and Speech Recognition
Language: en
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Deep Learning for NLP and Speech Recognition

Authors: Uday Kamath
Categories: Computers
Type: BOOK - Published: 2019-06-10 - Publisher: Springer

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This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Mode