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Speech/Music Classification Enhancement for 3GPP2 SMV Codec Based on Support Vector Machine
Sang-Kyun KIM
Joon-Hyuk CHANG
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E92-A No.2 pp.630-632
Publication Date: 2009/02/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Speech and Hearing
Keyword:
SVM,
SMV,
speech/music classification algorithm,
Full Text: PDF(163.6KB)
Summary:
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.
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