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Speech processing in mobile environments [electronic resource] / K. Sreenivasa Rao, Anil Kumar Vuppala.

Sreenivasa Rao, K., author.; Vuppala, Anil Kumar, author.
2014
TK7882.S65
Available Online
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Title
Speech processing in mobile environments [electronic resource] / K. Sreenivasa Rao, Anil Kumar Vuppala.
Author
Sreenivasa Rao, K., author.
ISBN
9783319031163 electronic book
3319031163 electronic book
9783319031156
DOI
https://doi.org/10.1007/978-3-319-03116-3
Published
Cham : Springer, 2014.
Language
English
Description
1 online resource (xii, 121 pages) : illustrations (some color).
Item Number
10.1007/978-3-319-03116-3 doi
Call Number
TK7882.S65
Dewey Decimal Classification
006.4/54
Summary
This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. The methods presented in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments. The authors provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral enhancement methods to minimize the effect of noise and examining methods and models on speech and speaker recognition applications in mobile environments.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from PDF title page (SpringerLink, viewed February 3, 2014).
Added Author
Vuppala, Anil Kumar, author.
Series
SpringerBriefs in Electrical and Computer Engineering. SpringerBriefs in speech technology, 2191-8112
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Background and Literature Review
Vowel Onset Point Detection from Coded and Noisy Speech
Consonant-Vowel Recognition in Presence of Coding and Background Noise
Spotting and Recognition of Consonant-Vowel Units from Continuous Speech
Speaker Identification and Time Scale Modification Using VOPs
Summary and Conclusions
MFCC Features
Speech Orders
Pattern Recognition Models.

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