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2015 | Book

Language Identification Using Spectral and Prosodic Features

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About this book

This book discusses the impact of spectral features extracted from frame level, glottal closure regions, and pitch-synchronous analysis on the performance of language identification systems. In addition to spectral features, the authors explore prosodic features such as intonation, rhythm, and stress features for discriminating the languages. They present how the proposed spectral and prosodic features capture the language specific information from two complementary aspects, showing how the development of language identification (LID) system using the combination of spectral and prosodic features will enhance the accuracy of identification as well as improve the robustness of the system. This book provides the methods to extract the spectral and prosodic features at various levels, and also suggests the appropriate models for developing robust LID systems according to specific spectral and prosodic features. Finally, the book discuss about various combinations of spectral and prosodic features, and the desired models to enhance the performance of LID systems.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
This chapter provides brief introduction about language identification and its applications. General issues in language identification, language-specific cues in speech signal, specific issues in identification of Indian languages, scope of the work, issues addressed and organization of the book are discussed in this chapter.
K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Chapter 2. Literature Review
Abstract
This chapter provides an overview of existing language identification systems. Existing language-specific features applied for LID study have been highlighted. The reasons for attraction towards developing implicit LID systems are explained and finally the motivation for the present work has been discussed.
K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Chapter 3. Language Identification Using Spectral Features
Abstract
This chapter introduces multilingual Indian language speech corpus consisting of 27 regional Indian languages for analyzing the language identification (LID) performance. Speaker-dependent and independent language models are also discussed in view of LID. Spectral features extracted from conventional block processing, pitch synchronous analysis, and glottal closure regions are examined for discriminating the languages.
K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Chapter 4. Language Identification Using Prosodic Features
Abstract
In previous chapter language-specific spectral features are discussed for language identification (LID). Present chapter mainly focuses on language-specific prosodic features at syllable, word and global levels for LID task. For improving the recognition accuracy of LID system further, combination of spectral and prosodic features has been explored.
K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Chapter 5. Summary and Conclusions
Abstract
This chapter summarizes the research work presented in this book. It highlights the major contributions of the book, and briefly portrays the direction for future scope of work.
K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
Backmatter
Metadata
Title
Language Identification Using Spectral and Prosodic Features
Authors
K. Sreenivasa Rao
V. Ramu Reddy
Sudhamay Maity
Copyright Year
2015
Electronic ISBN
978-3-319-17163-0
Print ISBN
978-3-319-17162-3
DOI
https://doi.org/10.1007/978-3-319-17163-0