基于2DFT变换的伴奏音乐分离方法

Accompaniment music separation using 2DFT transform

  • 摘要: 针对在单通道音乐分离过程中,伴奏难以分离且分离方法鲁棒性差的问题,提出一种基于二维傅里叶变换(2 Dimension Fourier Transform, 2DFT)的音乐伴奏分离方法。该方法首先对单通道音乐进行2DFT变换,将其变为二维声谱图,然后利用图像滤波的方式确定周期性峰值能量的位置,使用矩形窗构建掩蔽矩阵提取出伴奏音乐成分,最后通过短时傅里叶逆变换的方式,恢复出伴奏的时域信号。仿真实验表明,本文方法对比其他分离算法具有一定的优越性,可以将分离指标SIR提升0.5~4dB左右,鲁棒性SAR提升超过15dB。

     

    Abstract: For the difficulty of separation of accompaniment from mono music, a kind of music accompaniment separation method based on two-dimensional Fourier transform (2DFT) was proposed, first of all, mono music was transformed by two-dimensional Fourier transform into a two-dimensional sonogram. Secondly, the position of periodic peak energy was determined by image filtering, and then masking matrix was constructed by rectangular window to extract the constituent of the music accompaniment. Finally, the accompaniment of the time-domain signal was restored by means of inverse transformation. The simulation experiments show that the method in this paper has an advantage over other separation algorithm. The separation index SIR can be improved by about 0.5-4 dB, and SAR by more than 15dB.

     

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