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基于小波变换和支持向量机的音频分类
引用本文:郑继明,俞佳. 基于小波变换和支持向量机的音频分类[J]. 计算机工程与应用, 2009, 45(11): 158-161. DOI: 10.3778/j.issn.1002-8331.2009.11.048
作者姓名:郑继明  俞佳
作者单位:重庆邮电大学,应用数学研究所,重庆,400065;重庆邮电大学,计算机科学与技术学院,重庆,400065
基金项目:重庆市教育委员会科学技术研究项目 
摘    要:音频特征提取是音频分类的基础,而音频分类又是内容的音频检索的关键。综合分析了语音和音乐的区别性特征,提出一种基于小波变换和支持向量机的音频特征提取和分类的方法,用于纯语音、音乐、带背景音乐的语音以及环境音的分类,并且评估了新特征集合在SVM分类器上的分类效果。实验结果表明,提出的音频特征有效、合理,分类性能较好。

关 键 词:川、波变换  特征提取  音频分类  支持向量机
收稿时间:2008-03-03
修稿时间:2008-5-7 

Audio classification based on wavelet transform and support vector machine
ZHENG Ji-ming,YU Jia. Audio classification based on wavelet transform and support vector machine[J]. Computer Engineering and Applications, 2009, 45(11): 158-161. DOI: 10.3778/j.issn.1002-8331.2009.11.048
Authors:ZHENG Ji-ming  YU Jia
Affiliation:1.Institute of Applied Mathematics,Chongqing University of Posts and Telecommunications,Chongqing 400065,China 2.College of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
Abstract:Feature extraction is the foundation of audio classification,while audio classification is a key technology of content based audio retrieval.In this paper,discriminating features between speech and music are analyzed,the work on audio feature ex-traction and classification based on wavelet transform and Support Vector Machine(SVM) is presented.It is used to classify audio into pure speech,music,speech with music and environment sounds.The performance of some new proposed feature is evaluated.The experiments...
Keywords:wavelet transform  feature extraction  audio classification  Support Vector Machine(SVM)
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