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Language Identification Using Spectral and Prosodic Features

  • K. Sreenivasa Rao
  • V. Ramu Reddy
  • Sudhamay Maity

Part of the SpringerBriefs in Electrical and Computer Engineering book series

Also part of the SpringerBriefs in Speech Technology book sub series (BRIEFSSPEECHTECH)

Table of contents

  1. Front Matter
    Pages i-xi
  2. K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
    Pages 1-11
  3. K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
    Pages 13-26
  4. K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
    Pages 27-53
  5. K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
    Pages 55-81
  6. K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity
    Pages 83-86
  7. Back Matter
    Pages 87-98

About this book

Introduction

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.

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

Authors and affiliations

  • K. Sreenivasa Rao
    • 1
  • V. Ramu Reddy
    • 2
  • Sudhamay Maity
    • 3
  1. 1.Indian Institute of Technology KharagpurKharagpur, West BengalIndia
  2. 2.Innovation Lab KolkataKolkata, West BengalIndia
  3. 3.Indian Institute of Technology KharagpurKharagpur, West BengalIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-17163-0
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-17162-3
  • Online ISBN 978-3-319-17163-0
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • Buy this book on publisher's site
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