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Language Identification Using Spectral and Prosodic Features

紀錄類型:	書目-語言資料,印刷品 : 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.
面頁冊數:	XI, 98 p. 21 illus., 5 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Signal processing. -
電子資源:	https://doi.org/10.1007/978-3-319-17163-0
ISBN:	9783319171630

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. - 1st ed. 2015. - XI, 98 p. 21 illus., 5 illus. in color.online resource. - SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,2191-737X. - SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,.

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

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

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.382

Language Identification Using Spectral and Prosodic Features
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