Environmental Sound Classification using Hybrid SVM/KNN Classifier and MPEG-7 Audio Low-Level Descriptor

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.