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一种基于选择性集成SVM的新闻音频自动分类方法*

, PP. 634-639

Keywords: 音频自动分类,选择性集成,支持向量机,决策规则

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Abstract:

作为视频检索的一种重要线索,音频检测和分类受到广泛关注并已成为一个热门的研究方向.在新闻视频先验模型和结构的基础上,提出一种基于选择性集成SVM(SENSVM)的分类器设计方法.从而将新闻视频划分成静音、音乐、语音和带有背景音乐的语音这4种类型.用8514s的真实新闻音频数据所作的仿真实验结果表明:所提出基于选择性集成SVM的新闻音频自动分类算法的平均准确率高达98.2%,远远高于单纯基于SVM的方法和传统的基于门限的方法.

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