Title | ||
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New techniques for improving the practicality of an SVM-based speech/music classifier |
Abstract | ||
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Variable bit-rate coding introduced for effective utilization of limited communication bandwidth requires accurate classification of input signals. This paper investigates implementation of a support vector machine (SVM)-based speech/music classifier in the selectable mode vocoder (SMV) framework, which is a standard codec adopted by the Third-Generation Partnership Project 2 (3GPP2). A support vector machine is well known for its superior pattern recognition capability; however, it is accompanied by a high computational cost. In order to achieve a more practical system, three techniques are proposed for the SVM-based speech/music classifier. The first is to prune support vectors that least contribute to the output of the SVM, while the other two are aimed at reducing the number of classification requests to the SVM-based classifier by eliminating or redirecting some of the classification requests to the classifier. |
Year | DOI | Venue |
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2012 | 10.1109/ICASSP.2012.6288214 | ICASSP |
Keywords | Field | DocType |
classification algorithm,pattern recognition,speech recognition,third-generation partnership project 2,music,pattern classification,standard codec adoption,selectable mode vocoder framework,variable bit-rate coding,communication bandwidth utilization,vocoders,input signal classification,support vector machine,3g mobile communication,codecs,3gpp2,speech coding,embedded software,svm-based speech-music classifier,smv framework,support vector machines,speech,vectors,radiation detectors,kernel,accuracy | Structured support vector machine,Speech coding,Selectable Mode Vocoder,Computer science,Artificial intelligence,Classifier (linguistics),Codec,Pattern recognition,Support vector machine,Speech recognition,Margin classifier,Machine learning,Quadratic classifier | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4673-0044-5 | 978-1-4673-0044-5 | 1 |
PageRank | References | Authors |
0.38 | 4 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Chungsoo Lim | 1 | 39 | 4.35 |
Seong-Ro Lee | 2 | 16 | 7.48 |
Yeonwoo Lee | 3 | 66 | 14.13 |
Joon-Hyuk Chang | 4 | 1 | 0.38 |