抄録
In this letter, we propose a novel approach to speech/music classification based on the support vector machine (SVM) to improve the performance of the 3GPP2 selectable mode vocoder (SMV) codec. We first analyze the features and the classification method used in real time speech/music classification algorithm in SMV, and then apply the SVM for enhanced speech/music classification. For evaluation of performance, we compare the proposed algorithm and the traditional algorithm of the SMV. The performance of the proposed system is evaluated under the various environments and shows better performance compared to the original method in the SMV.
