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融合GMM及SVM的特定音频事件高精度识别方法

Keywords: 音频识别,高斯混合模型(GMM),支持向量机(SVM),Mel频率倒谱系数(MFCC),特定音频事件

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Abstract:

针对特定音频事件识别中持续时间特别短的音频事件漏检概率高、识别速度较慢的问题,提出一种融合高斯混合模型(GMM)及支持向量机(SVM)的特定音频事件识别算法.该方法利用GMM的统计分布描述能力和SVM的推广泛化能力,将GMM和SVM分别识别的结果进行融合处理,以手枪、步枪、机关枪等10类以上枪声为实验数据,无需针对每种枪声生成相应的识别模板,仅需训练生成2个识别模板.实验结果表明,识别准确率达到92.71%.该方法模板数量少,不需要多次训练,算法复杂度较低,不仅便于应用而且可大幅提升识别效率.

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