An Improved Audio Classification Algorithm using SVM Weight Factor

摘要

As the demands and usage for audio classification and retrieval increase, the classification methods need to be improved to be more automatic and effective. The traditional text-based audio classification fails to recognize the underlying content of audio files. In this paper we propose a new hybrid audio classification algorithm based on SVM weight factor and Euclidean distance in order to improve the accuracy for audio classification. The proposed algorithm can extract the weight factor from Supporting Vector classification Model (SVM) and apply it to the Euclidean measurement. The experimental results show that it can improve the audio classification accuracy by 28% at the maximum and 7% in the overall performance. By using the new proposed algorithm, some mis-classified audio data from a conventional Euclidean distance classifier can be classified.