Overview
- Discusses recently proposed spectral features extracted from glottal closure regions and pitch-synchronous analysis, which are more robust and carry high degree of language discrimination information
- Proposes robust methods for extracting the spectral features from glottal closure regions and pitch-synchronous analysis
- Investigates spectral features for language identification tasks in noisy background environments
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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Table of contents (5 chapters)
Keywords
- Combination of Spectral and Prosodic Features for LID
- Intonation, Rhythm and Stress Features for LID
- LID Using Pitch-synchronous Spectral Features
- LID Using Spectral Features from Glottal Closure Regions
- Language Identification Using Multilevel Prosodic Features
- Language Identification from Speech
- Language Identification using Multi-level Spectral Features
- Language Identification using Prosodic Features
- Language Identification using Spectral Features
- Language Recognition from Speech
- Spectral and Prosodic Features for Language Identification
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Language Identification Using Spectral and Prosodic Features
Authors: K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-3-319-17163-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2015
Softcover ISBN: 978-3-319-17162-3Published: 09 April 2015
eBook ISBN: 978-3-319-17163-0Published: 31 March 2015
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: XI, 98
Number of Illustrations: 16 b/w illustrations, 5 illustrations in colour
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Computational Linguistics