Overview
- Discusses the excitation source component in the context of language identification, detailing how it can exploited for language discrimination in speech
- Proposes robust signal processing methods for extracting the implicit excitation source features from LP residual signal
- Presents explicit parametric features for representing the excitation source component of speech
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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Table of contents (6 chapters)
Keywords
- Anguage Identification
- Combination of Spectral and Source Features
- Implicit and Explicit Source Features for LID
- Lang. Identification using Implicit Exci. Source Features
- Language Identification from Speech
- Language Identification using Excitation Source Features
- Language Identification using Source Features
- Language Recognition from Speech
- Magnitude and Phase Components of LP
- Parametric Excitation Source Features for Lang. Identification
- RMFCC and MPDSS Features for LID
- Residual for LID
- Sub-segmental, Segmental and
- Suprasegmental Source Features for
- for LID
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Language Identification Using Excitation Source Features
Authors: K. Sreenivasa Rao, Dipanjan Nandi
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-3-319-17725-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2015
Softcover ISBN: 978-3-319-17724-3Published: 23 April 2015
eBook ISBN: 978-3-319-17725-0Published: 15 April 2015
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: XII, 119
Number of Illustrations: 16 b/w illustrations, 3 illustrations in colour
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Computational Linguistics