| 曾金芳,黄费贞,白冰,徐林涛.基于耳蜗谱图纹理特征的声音事件识别[J].声学技术,2020,39(1):69~75 |
| 基于耳蜗谱图纹理特征的声音事件识别 |
| Sound event recognition based on texture features of cochleagram |
| 投稿时间：2019-01-05 修订日期：2019-02-25 |
| DOI：10.16300/j.cnki.1000-3630.2020.01.012 |
| 中文关键词: Gammatone滤波器组 耳蜗谱图 Curvelet变换 完全局部二值模式 支持向量机 |
| 英文关键词: Gammatone filter bank cochleagram Curvelet transform completed local binary pattern support vector machine |
| 基金项目:湖南省自然科学基金项目（2018JJ3486）、湘潭大学校级科研项目（16XZX02）、湘潭大学博士启动项目（15QDZ28） |
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| 中文摘要: |
| 针对在各种环境下声音事件的识别问题，提出了一种基于谱图纹理特征的声音事件识别方法。首先，将声音信号通过伽马通（Gammatone）滤波器组，使原始声音样本转化为灰度耳蜗谱图；然后，对谱图进行曲波（Curvelet）变换，得到不同尺度、不同方向的Curvelet子带；再采用改进完全局部二值模式（Improved Completed Local Binary Pattern，ICLBP）提取Curvelet子带的纹理特征，并生成分块统计直方图，将统计直方图级联作为一种新的声音事件特征；最后，使用支持向量机作为分类器对16种声音事件在不同噪声和不同信噪比下进行识别。实验结果表明，所提特征与其他声音特征相比，可以有效识别各种噪声环境下不同种类的声音事件。 |
| 英文摘要: |
| A sound event recognition method based on texture features of cochleagram is proposed for improving sound event recognition in various environments. Firstly, the original sound sample is converted into a grayscale cochleagram by Gammatone filter bank. Then, the cochleagram is processed by Curvelet transform to obtain Curvelet sub-bands with different scales and directions. The texture features of Curvelet sub-bands are extracted by using the improved completed local binary pattern (ICLBP) to generate the block statistical histograms which are cascaded as a new sound event feature for recognition. Finally, the support vector machine is used as a classifier to identify 16 kinds of sound events under different noise environments and different signal-to-noise ratios. The experimental results show that the proposed algorithm can effectively identify different kinds of sound events in various noise environments compared with other sound features. |
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