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An Insect Song Signal Feature Extraction Method Based on the Wavelet Packet Analysis

机译:基于小波包分析的昆虫歌曲信号特征提取方法

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The wavelet packet decomposition method was used to two common insects song signal. Frequency decomposition and feature extraction were made, the feature vectors, eigenvalues and the sound quality evaluation parameter vectors were constructed, then the correlation analysis calculation were made between the eigenvalues and the sound quality evaluation parameter vectors. The results show that the correlation coefficients are good, the average correlation coefficients of cricket and grasshopper song signals are 0.8875 and 0.6942, the results of cricket is much better than grasshopper, it proved that the proposed algorithm is more suitable for cricket song signals analysis, a new and effective sound quality evaluation method for typical insect with friction sound mechanism is provided.
机译:小波分组分解方法用于两个常见的昆虫歌曲信号。制作了频率分解和特征提取,构建了特征向量,特征值和音质评估参数向量,然后在特征值和音质评估参数向量之间进行相关分析计算。结果表明,相关系数好,板球和蚱蜢歌曲信号的平均相关系数为0.8875和0.6942,蟋蟀结果比蚱蜢要好得多,证明该算法更适合板球歌曲信号分析,提供了一种具有摩擦声机制的典型昆虫的新有效的音质评价方法。

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