MFCC combined with sparse coding for sound event classification under different noise environments

DOI

10.2991/eeeis-16.2017.50How to use a DOI?

Keywords

Sound event classification; MFCC; Sparse coding.

Abstract

In recent years, the most popular method for sound event classification can be classified into two types: 1) Extract MFCC or PLP, then train classifier for classification; 2) Convert sound into spectrogram, then use the method of image classification. However, the two methods have not achieved satisfied performance. In order to improve the classification performance, we present a sound event classification method based on MFCC and sparse coding which provides a class of effective algorithms to capture the high-level representation features of the input data. Sparse coding coefficients will be used as the sound event features to train the classification model. Our experimental results demonstrate the great robustness, adaptability and an obvious improvement in sound event classification.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jia-Min Mao
AU  - Yun-Peng Wu
AU  - Li-Yang Liu
AU  - Wei-Feng Li
PY  - 2016/12
DA  - 2016/12
TI  - MFCC combined with sparse coding for sound event classification under different noise environments
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 386
EP  - 394
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.50
DO  - 10.2991/eeeis-16.2017.50
ID  - Mao2016/12
ER  -