FEATURE EXTRACTION AND CLASSIFICATION FOR AUDIO INFORMATION IN NEWS VIDEO

被引：14

作者：

Song, Yu ^{[1
]}

Wang, Wen-Hong ^{[1
]}

Guo, Feng-Juan ^{[2
]}

机构：

[1] North China Elect Power Univ, Dept Comp, Baoding 071003, Peoples R China

[2] North China Elect Power Univ, Coll Sci & Technol, Baoding 071003, Peoples R China

来源：

PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION | 2009年

关键词：

News video; Audio classification; Feature extraction; Decision rules;

D O I：

10.1109/ICWAPR.2009.5207452

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Feature extraction and analysis are the foundation of audio classification. At first, audio features are analyzed deeply, including short-time energy, zero-crossing rate, bandwidth, low short-time energy ratio, high zero-crossing rate ratio, and noise rate. Secondly a new audio classification method for news video is proposed based on the decision tree method, and then divides audio information into four classes: silence, pure speech, music, non-pure speech. The experiment results show that the selected features are effective for audio classification in news video, and the classification accuracy is reasonable.

引用

页码：43 / +

页数：3

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