1.

Record Nr.

UNINA9910299485503321

Autore

Rao K. Sreenivasa (Krothapalli Sreenivasa)

Titolo

Speech Processing in Mobile Environments / / by K. Sreenivasa Rao, Anil Kumar Vuppala

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014

ISBN

3-319-03116-3

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (129 p.)

Collana

SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, , 2191-737X

Disciplina

006.454

Soggetti

Signal processing

Image processing

Speech processing systems

Computers

Electrical engineering

Signal, Image and Speech Processing

Information Systems and Communication Service

Communications Engineering, Networks

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction -- 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.

Sommario/riassunto

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.