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A hierarchical approach for speech-instrumental-song classification
Audio classification acts as the fundamental step for lots of applications like content based audio retrieval and audio indexing. In this work, we have presented a novel scheme for classifying audio signal into three categories namely, speech, music without voice (instrumental) and music with voice...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4322669/ https://www.ncbi.nlm.nih.gov/pubmed/25694856 http://dx.doi.org/10.1186/2193-1801-2-526 |
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author | Ghosal, Arijit Chakraborty, Rudrasis Dhara, Bibhas Chandra Saha, Sanjoy Kumar |
author_facet | Ghosal, Arijit Chakraborty, Rudrasis Dhara, Bibhas Chandra Saha, Sanjoy Kumar |
author_sort | Ghosal, Arijit |
collection | PubMed |
description | Audio classification acts as the fundamental step for lots of applications like content based audio retrieval and audio indexing. In this work, we have presented a novel scheme for classifying audio signal into three categories namely, speech, music without voice (instrumental) and music with voice (song). A hierarchical approach has been adopted to classify the signals. At the first stage, signals are categorized as speech and music using audio texture derived from simple features like ZCR and STE. Proposed audio texture captures contextual information and summarizes the frame level features. At the second stage, music is further classified as instrumental/song based on Mel frequency cepstral co-efficient (MFCC). A classifier based on Random Sample and Consensus (RANSAC), capable of handling wide variety of data has been utilized. Experimental result indicates the effectiveness of the proposed scheme. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2193-1801-2-526) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4322669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-43226692015-02-18 A hierarchical approach for speech-instrumental-song classification Ghosal, Arijit Chakraborty, Rudrasis Dhara, Bibhas Chandra Saha, Sanjoy Kumar Springerplus Methodology Audio classification acts as the fundamental step for lots of applications like content based audio retrieval and audio indexing. In this work, we have presented a novel scheme for classifying audio signal into three categories namely, speech, music without voice (instrumental) and music with voice (song). A hierarchical approach has been adopted to classify the signals. At the first stage, signals are categorized as speech and music using audio texture derived from simple features like ZCR and STE. Proposed audio texture captures contextual information and summarizes the frame level features. At the second stage, music is further classified as instrumental/song based on Mel frequency cepstral co-efficient (MFCC). A classifier based on Random Sample and Consensus (RANSAC), capable of handling wide variety of data has been utilized. Experimental result indicates the effectiveness of the proposed scheme. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2193-1801-2-526) contains supplementary material, which is available to authorized users. Springer International Publishing 2013-10-17 /pmc/articles/PMC4322669/ /pubmed/25694856 http://dx.doi.org/10.1186/2193-1801-2-526 Text en © Ghosal et al.; licensee Springer. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Ghosal, Arijit Chakraborty, Rudrasis Dhara, Bibhas Chandra Saha, Sanjoy Kumar A hierarchical approach for speech-instrumental-song classification |
title | A hierarchical approach for speech-instrumental-song classification |
title_full | A hierarchical approach for speech-instrumental-song classification |
title_fullStr | A hierarchical approach for speech-instrumental-song classification |
title_full_unstemmed | A hierarchical approach for speech-instrumental-song classification |
title_short | A hierarchical approach for speech-instrumental-song classification |
title_sort | hierarchical approach for speech-instrumental-song classification |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4322669/ https://www.ncbi.nlm.nih.gov/pubmed/25694856 http://dx.doi.org/10.1186/2193-1801-2-526 |
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