Language Identification Using Spectral and Prosodic Features

1. Front Matter

   Pages i-xi

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2. Introduction

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

   Pages 1-11

3. Literature Review

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

   Pages 13-26

4. Language Identification Using Spectral Features

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

   Pages 27-53

5. Language Identification Using Prosodic Features

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

   Pages 55-81

6. Summary and Conclusions

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

   Pages 83-86

7. Back Matter

   Pages 87-98

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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.

• 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

• Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

  K. Sreenivasa Rao, Sudhamay Maity

• Innovation Lab Kolkata, Kolkata, West Bengal, India

  V. Ramu Reddy

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