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Environmental sound classification based on time-frequency representation

机译:基于时频表示的环境声分类

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摘要

This paper proposes a feature extraction method for environmental sound event classification based on time-frequency representation such as spectrogram. There are three portions to perform environmental classification. Firstly, the input signal is converted into spectrogram image with time-frequency representation using short time Fourier transforms. Secondly, this spectrogram is used to extract features with local binary pattern of three different radius and neighborhood sizes. The three distinct features resulted from local binary pattern based on spectrogram are concatenated and used as one feature vector. Finally, multi support vector machine is used for classification of environmental sound event. Evaluation is tested on ESC-10 dataset.
机译:提出了一种基于时频表示的环境声事件分类特征提取方法,如声谱图。分为三个部分进行环境分类。首先,使用短时傅立叶变换将输入信号转换为具有时频表示的频谱图图像。其次,该频谱图用于提取具有三个不同半径和邻域大小的局部二进制模式的特征。由基于频谱图的局部二进制模式产生的三个不同特征被连接起来并用作一个特征向量。最后,将多支持向量机用于环境声事件的分类。评估在ESC-10数据集上进行测试。

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