@inproceedings{2f637ec5c2d2419185299d39f8640185,
title = "Automatic recognition of audio event using dynamic local binary patterns",
abstract = "This work proposes an automatic recognition system for recognizing audio events. First, an audio signal is converted into a spectrogram by short time Fourier transform. The acoustic background noises in the spectrogram are reduced by box filtering. The contrast of the spectrogram is then enhanced by VAR operation. With the enhanced spectrogram, this work further proposes a novel dynamic local binary pattern (DLBP) feature based on human auditory system. Finally, the DLBP features are fed to multi-class support vector machines to achieve the audio event recognition. The experimental results on 16 classes of audio events demonstrate the performance of the proposed audio event recognition system.",
keywords = "Auditory system, Feature extraction, Filtering, Pattern recognition, Spectrogram, Speech, Support vector machines",
author = "Wang, {Chien Yao} and Chin, {Yu Hao} and Tai, {Tzu Chiang} and David Gunawan and Wang, {Jia Ching}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 ; Conference date: 06-06-2015 Through 08-06-2015",
year = "2015",
month = aug,
day = "20",
doi = "10.1109/ICCE-TW.2015.7216879",
language = "???core.languages.en_GB???",
series = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "246--247",
booktitle = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
}