@inproceedings{4a7fdd8b96ae4eeea66b3c5ad6c9e368,
title = "Environmental sound classification using hybrid SVM/KNN classifier and MPEG-7 audio low-level descriptor",
abstract = "In this paper, we present a new environmental sound classification architecture. The proposed sound classifier is performed in frame level and fuses the support vector machine (SVM) and the k nearest neighbor rule (KNN). In feature selection, three MPEG-7 audio low-level descriptors, spectrum centroid, spectrum spread, and spectrum flatness are used as the sound features to exploit their ability in sound classification. Experiments carried out on a 12-class sound database can achieve an 85.1% accuracy rate. The performance comparison between the HMM sound classifier using audio spectrum projection features demonstrates the superiority of the proposed scheme.",
author = "Wang, {Jia Ching} and Wang, {Jhing Fa} and He, {Kuok Wai} and Hsu, {Cheng Shu}",
year = "2006",
language = "???core.languages.en_GB???",
isbn = "0780394909",
series = "IEEE International Conference on Neural Networks - Conference Proceedings",
pages = "1731--1735",
booktitle = "International Joint Conference on Neural Networks 2006, IJCNN '06",
note = "International Joint Conference on Neural Networks 2006, IJCNN '06 ; Conference date: 16-07-2006 Through 21-07-2006",
}