Determined BSS Based on Time-Frequency Masking and Its Application to Harmonic Vector Analysis
Determined BSS Based on Time-Frequency Masking and Its Application to Harmonic Vector Analysis
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DOI：
10.1109/taslp.2021.3073863
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发表时间：
2020-04
期刊：
影响因子：
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通讯作者：
K. Yatabe;Daichi Kitamura
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文献类型：
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作者：
K. Yatabe;Daichi Kitamura
本文提出了基于音频盲源分离（BSS）通用算法框架的谐波矢量分析（HVA），该算法框架也在本文中提出。当麦克风和源的数量相等时（确定的情况），卷积音频混合的 BSS 通常通过多通道线性滤波来执行。本文解决了基于批处理确定的 BSS。为了估计去混频滤波器，源信号的有效建模非常重要。一个成功的例子是独立矢量分析 (IVA)，它通过每个源中的频率分量之间的共现对信号进行建模。为了给源建模更多的自由，本文提出了确定BSS的通用框架。它基于使用原始对偶分裂算法的即插即用方案，使我们能够通过时频掩模隐式地对源信号进行建模。通过使用所提出的框架，可以通过设计增强源信号的掩模来开发确定的 BSS 算法。作为其应用的一个例子，我们通过定义时频掩模来提出 HVA，该掩模通过倒谱的稀疏性来增强音频信号的谐波结构。实验表明，对于语音和音乐信号，HVA 的性能优于 IVA 和独立低秩矩阵分析 (ILRMA)。论文中还提供了 MATLAB 代码以供参考。
This paper proposes harmonic vector analysis (HVA) based on a general algorithmic framework of audio blind source separation (BSS) that is also presented in this paper. BSS for a convolutive audio mixture is usually performed by multichannel linear filtering when the numbers of microphones and sources are equal (determined situation). This paper addresses such determined BSS based on batch processing. To estimate the demixing filters, effective modeling of the source signals is important. One successful example is independent vector analysis (IVA) that models the signals via co-occurrence among the frequency components in each source. To give more freedom to the source modeling, a general framework of determined BSS is presented in this paper. It is based on the plug-and-play scheme using a primal-dual splitting algorithm and enables us to model the source signals implicitly through a time-frequency mask. By using the proposed framework, determined BSS algorithms can be developed by designing masks that enhance the source signals. As an example of its application, we propose HVA by defining a time-frequency mask that enhances the harmonic structure of audio signals via sparsity of cepstrum. The experiments showed that HVA outperforms IVA and independent low-rank matrix analysis (ILRMA) for both speech and music signals. A MATLAB code is provided along with the paper for a reference.