Complex ratio masking for singing voice separation

Yixuan Zhang; Yuzhou Liu; DeLiang Wang

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arXiv · 2011.02008

Complex ratio masking for singing voice separation

Yixuan Zhang·Yuzhou Liu·DeLiang Wang

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Abstract

Music source separation is important for applications such as karaoke and remixing. Much of previous research focuses on estimating short-time Fourier transform (STFT) magnitude and discarding phase information. We observe that, for singing voice separation, phase can make considerable improvement in separation quality. This paper proposes a complex ratio masking method for voice and accompaniment separation. The proposed method employs DenseUNet with self attention to estimate the real and imaginary components of STFT for each sound source. A simple ensemble technique is introduced to further improve separation performance. Evaluation results demonstrate that the proposed method outperforms recent state-of-the-art models for both separated voice and accompaniment.

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Yixuan Zhang, Yuzhou Liu, DeLiang Wang. 2020-11-03. Complex ratio masking for singing voice separation. https://arxiv.org/abs/2011.02008

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