基于Log-Gabor滤波器和多类支持向量机的环境声谱图分类
Environmental Sounds Spectrogram Classification using Log-Gabor Filters and Multiclass Support Vector Machines
摘要：
提出了一种基于环境声幅谱图的高效特征提取新方法。我们提出了基于视觉域的方法。这种方法包括三种方法。第一种方法是基于提取每个频谱图的一个单一的log-Gabor滤波器，然后是互信息过程。在第二种方法中，频谱图通过与第一种方法相同的步骤，但是具有12个对数Gabor滤波器的平均组。第三种方法是将声谱图分割成三块，然后对每个声谱图块应用第二种方法。分类结果表明，第二种方法是我们的环境声音分类系统中最有效的。
英文摘要：
This paper presents novel approaches for efficient feature extraction using environmental sound magnitude spectrogram. We propose approach based on the visual domain. This approach included three methods. The first method is based on extraction for each spectrogram a single log-Gabor filter followed by mutual information procedure. In the second method, the spectrogram is passed by the same steps of the first method but with an averaged bank of 12 log-Gabor filter. The third method consists of spectrogram segmentation into three patches, and after that for each spectrogram patch we applied the second method. The classification results prove that the second method is the most efficient in our environmental sound classification system.
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