Feature analysis for audio classification
In this work we analyze and implement several audio features. We emphasize our analysis on the ZCR feature and propose a modification making it more robust when signals are near zero. They are all used to discriminate the following audio classes: music, speech, environmental sound. An SVM classifier...
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| Formato: | SER |
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p239_Bengolea |
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todo:paper_03029743_v8827_n_p239_Bengolea2023-10-03T15:19:39Z Feature analysis for audio classification Bengolea, G. Acevedo, D. Rais, M. Mejail, M. Hancock E. Bayro-Corrochano E. Computer vision Pattern recognition Audio class Audio classification Audio features Classification tool Environmental sounds Fast classification Feature analysis SVM classifiers Audio acoustics In this work we analyze and implement several audio features. We emphasize our analysis on the ZCR feature and propose a modification making it more robust when signals are near zero. They are all used to discriminate the following audio classes: music, speech, environmental sound. An SVM classifier is used as a classification tool, which has proven to be efficient for audio classification. By means of a selection heuristic we draw conclusions of how they may be combined for fast classification. © Springer International Publishing Switzerland 2014. SER info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p239_Bengolea |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Computer vision Pattern recognition Audio class Audio classification Audio features Classification tool Environmental sounds Fast classification Feature analysis SVM classifiers Audio acoustics |
| spellingShingle |
Computer vision Pattern recognition Audio class Audio classification Audio features Classification tool Environmental sounds Fast classification Feature analysis SVM classifiers Audio acoustics Bengolea, G. Acevedo, D. Rais, M. Mejail, M. Hancock E. Bayro-Corrochano E. Feature analysis for audio classification |
| topic_facet |
Computer vision Pattern recognition Audio class Audio classification Audio features Classification tool Environmental sounds Fast classification Feature analysis SVM classifiers Audio acoustics |
| description |
In this work we analyze and implement several audio features. We emphasize our analysis on the ZCR feature and propose a modification making it more robust when signals are near zero. They are all used to discriminate the following audio classes: music, speech, environmental sound. An SVM classifier is used as a classification tool, which has proven to be efficient for audio classification. By means of a selection heuristic we draw conclusions of how they may be combined for fast classification. © Springer International Publishing Switzerland 2014. |
| format |
SER |
| author |
Bengolea, G. Acevedo, D. Rais, M. Mejail, M. Hancock E. Bayro-Corrochano E. |
| author_facet |
Bengolea, G. Acevedo, D. Rais, M. Mejail, M. Hancock E. Bayro-Corrochano E. |
| author_sort |
Bengolea, G. |
| title |
Feature analysis for audio classification |
| title_short |
Feature analysis for audio classification |
| title_full |
Feature analysis for audio classification |
| title_fullStr |
Feature analysis for audio classification |
| title_full_unstemmed |
Feature analysis for audio classification |
| title_sort |
feature analysis for audio classification |
| url |
http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p239_Bengolea |
| work_keys_str_mv |
AT bengoleag featureanalysisforaudioclassification AT acevedod featureanalysisforaudioclassification AT raism featureanalysisforaudioclassification AT mejailm featureanalysisforaudioclassification AT hancocke featureanalysisforaudioclassification AT bayrocorrochanoe featureanalysisforaudioclassification |
| _version_ |
1782026167092510720 |