Details

Title Techniques for Noise Robustness in Automatic Speech Recognition
Author Virtanen, Tuomas
Binding Hardback
Edition number 1st
Edition Illustrated
Condition New
Pages 514
Volumes 1
Language ENG
Publisher Wiley
Publication date 2012-11-28
Illustrated Yes
Features Bibliography, Illustrated, Index, Table of Contents
Bookseller's Inventory # DADAX1119970881
ISBN 9781119970880 / 1119970881
Weight 2 lbs (0.91 kg)
Dimensions 9.8 x 6.9 x 1.1 in (24.89 x 17.53 x 2.79 cm)
Size 6.75x1.00x9.75
Category Technology & Industrial Arts
Library of Congress subjects Automatic speech recognition
Library of Congress Catalogue Number 2012025172
Dewey Decimal Code 006.454
Quantity available 1

About Ergodebooks Texas, United States

Specialising in: Rare Books, Rare Dvd, Rare Video, Textbook

Biblio member since 2005

Our goal is to provide best customer service and good condition books for the lowest possible price. We are always honest about condition of book. We list book only by ISBN # and hence exact book is guaranteed.

Terms of Sale:

We have 30 day return policy.

Browse books from Ergodebooks

Reader reviews for Techniques for Noise Robustness in Automatic Speech Recognition

Write a review for this book

Important Terms and Guidelines

Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
Reviews must be at least 140 characters in length.
Please do not reveal critical plot elements.
This is not a help line. Contact customer support if you need help.

Your review must not include:

Obscenities, discriminatory language, or other insulting language not suitable for public domain
Advertisements, “spam” content, or references to other products, offers or websites.
Email addresses, URLs, phone numbers, physical addresses or other contact information.
Overly critical comments about other reviews or reviewers
Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
Availability, price, or alternative ordering/shipping information

From the publisher

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences.

Key features:

Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech.
Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments.
Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR.
Includes contributions from top ASR researchers from leading research units in the field

From the rear cover

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences.

Key features:

Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech.
Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments.
Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR.
Includes contributions from top ASR researchers from leading research units in the field.

About the author

Tuomas Virtanen, Tampere University of Technology, FinlandDr . Virtanen is a senior researcher at Tampere University of Technology. Previously, he has worked at Cambridge University, UK as a research associate. His main research contributions are in sound source separation and its application to robust speech recognition, audio content analysis, and music information retrieval. He is well-known for his work on non-negative matrix factorization based source separation, which is currently widely used in the field. He has published numerous journal and conference articles related to above topics.

Rita Singh, Carnegie Mellon University, USA
Dr. Singh is the CEO of a speech-technology startup but remains an adjunct faculty of the Language Technologies Institute at Carnegie Mellon University. She has been a major contributor to the open-source CMU sphinx and is one of the main architects of the popular Sphinx4 java-based open-source speech recognition system. In addition to her work on core speech recognition technology, she has also developed several algorithms for noise compensation, and was the prime architect of CMU's award-winning submission to the 2001 Naval Research Lab's challenge on automatic recognition of speech in noisy environments (SPINE).

Bhiksha Raj, Carnegie Mellon University, USA
Dr. Raj is an associate professor in the Language Technologies Institute and in Electrical and Computer Engineering at Carnegie Mellon University. He has worked extensively on robustness algorithms for speech recognition, and is very well-known for his contributions to the highly-popular VTS approach for noise compensation, as well as his contributions to missing-feature-based techniques for noise compensation. He has published extensively on and holds patents for algorithms for microphone array processing and signal separation.

BIBLIO is the largest independent book marketplace in the world, with over 100 million books.