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Language Identification Using Spectral and Prosodic Features

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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.

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Series Title

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Call Number

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Publisher

Cham : ., 2015

Collation

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Language

English

ISBN/ISSN

978-3-319-17163-0

Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Computational Linguistics

Specific Detail Info

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Statement of Responsibility

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

Other Information

Cataloger

Kholif Basri

Source

https://link.springer.com/book/10.1007/978-3-319-17163-0

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