Cargando…

Language identification using spectral and prosodic features

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 stres...

Descripción completa

Detalles Bibliográficos
Autores principales: Rao, K Sreenivasa, Reddy, V Ramu, Maity, Sudhamay
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-17163-0
http://cds.cern.ch/record/2005811
_version_ 1780946223968026624
author Rao, K Sreenivasa
Reddy, V Ramu
Maity, Sudhamay
author_facet Rao, K Sreenivasa
Reddy, V Ramu
Maity, Sudhamay
author_sort Rao, K Sreenivasa
collection CERN
description 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.
id cern-2005811
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
publisher Springer
record_format invenio
spelling cern-20058112021-04-21T20:24:29Zdoi:10.1007/978-3-319-17163-0http://cds.cern.ch/record/2005811engRao, K SreenivasaReddy, V RamuMaity, SudhamayLanguage identification using spectral and prosodic featuresEngineeringThis 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.Springeroai:cds.cern.ch:20058112015
spellingShingle Engineering
Rao, K Sreenivasa
Reddy, V Ramu
Maity, Sudhamay
Language identification using spectral and prosodic features
title Language identification using spectral and prosodic features
title_full Language identification using spectral and prosodic features
title_fullStr Language identification using spectral and prosodic features
title_full_unstemmed Language identification using spectral and prosodic features
title_short Language identification using spectral and prosodic features
title_sort language identification using spectral and prosodic features
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-17163-0
http://cds.cern.ch/record/2005811
work_keys_str_mv AT raoksreenivasa languageidentificationusingspectralandprosodicfeatures
AT reddyvramu languageidentificationusingspectralandprosodicfeatures
AT maitysudhamay languageidentificationusingspectralandprosodicfeatures