Daniel Acevedo

Feature Analysis for Audio Classification

2014, Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2014
Citas: 1
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Autor(es)

Gaston Bengolea and Daniel Acevedo and Martín Rais and Marta Mejail

Abstract

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.

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