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Language identification using spectr...

Rao, K. Sreenivasa.

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Language identification using spectral and prosodic features

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Language identification using spectral and prosodic features/ by K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity.
作者:	Rao, K. Sreenivasa.
其他作者:	Reddy, V. Ramu.
出版者:	Cham :Springer International Publishing : : 2015.,
面頁冊數:	xi, 98 p. :ill., digital ;24 cm.
內容註:	Introduction -- Literature Review -- Language Identification using Spectral Features -- Language Identification using Prosodic Features -- Summary and Conclusions -- Appendix A: LPCC Features -- Appendix B: MFCC Features -- Appendix C: Gaussian Mixture Model (GMM)
Contained By:	Springer eBooks
標題:	Linguistic analysis (Linguistics) -
標題:	India -
電子資源:	http://dx.doi.org/10.1007/978-3-319-17163-0
ISBN:	9783319171630 (electronic bk.)

Language identification using spectral and prosodic features
Rao, K. Sreenivasa.

Language identification using spectral and prosodic features[electronic resource] /by K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity. - Cham :Springer International Publishing :2015. - xi, 98 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..

Introduction -- Literature Review -- Language Identification using Spectral Features -- Language Identification using Prosodic Features -- Summary and Conclusions -- Appendix A: LPCC Features -- Appendix B: MFCC Features -- Appendix C: Gaussian Mixture Model (GMM)

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.

ISBN: 9783319171630 (electronic bk.)

Standard No.: 10.1007/978-3-319-17163-0doiSubjects--Topical Terms:

598035
Linguistic analysis (Linguistics)
Subjects--Geographical Terms:

739969
India

LC Class. No.: PF1529

Dewey Class. No.: 491.1

Language identification using spectral and prosodic features
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505 0 $a Introduction -- Literature Review -- Language Identification using Spectral Features -- Language Identification using Prosodic Features -- Summary and Conclusions -- Appendix A: LPCC Features -- Appendix B: MFCC Features -- Appendix C: Gaussian Mixture Model (GMM)
520 $a 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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650 2 4 $a Language Translation and Linguistics. $3 892561
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700 1 $a Reddy, V. Ramu. $3 2139419
700 1 $a Maity, Sudhamay. $3 2139420
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