SPGM: Prioritizing Local Features for enhanced speech separation performance

Jia Qi Yip; Shengkui Zhao; Yukun Ma; Chongjia Ni; Chong Zhang; Hao Wang; Trung Hieu Nguyen; Kun Zhou; Dianwen Ng; Eng Siong Chng; Bin Ma

arXiv · 2309.12608

SPGM: Prioritizing Local Features for enhanced speech separation performance

Jia Qi Yip·Shengkui Zhao·Yukun Ma·Chongjia Ni·Chong Zhang·Hao Wang·Trung Hieu Nguyen·Kun Zhou·Dianwen Ng·Eng Siong Chng·Bin Ma

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Abstract

Dual-path is a popular architecture for speech separation models (e.g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separately model intra-chunk local features and inter-chunk global relationships. However, it has been found that inter-blocks, which comprise half a dual-path model's parameters, contribute minimally to performance. Thus, we propose the Single-Path Global Modulation (SPGM) block to replace inter-blocks. SPGM is named after its structure consisting of a parameter-free global pooling module followed by a modulation module comprising only 2% of the model's total parameters. The SPGM block allows all transformer layers in the model to be dedicated to local feature modelling, making the overall model single-path. SPGM achieves 22.1 dB SI-SDRi on WSJ0-2Mix and 20.4 dB SI-SDRi on Libri2Mix, exceeding the performance of Sepformer by 0.5 dB and 0.3 dB respectively and matches the performance of recent SOTA models with up to 8 times fewer parameters. Model and weights are available at huggingface.co/yipjiaqi/spgm

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Jia Qi Yip, Shengkui Zhao, Yukun Ma, Chongjia Ni, Chong Zhang, Hao Wang, Trung Hieu Nguyen, Kun Zhou, Dianwen Ng, Eng Siong Chng, Bin Ma. 2024-03-11. SPGM: Prioritizing Local Features for enhanced speech separation performance. https://arxiv.org/abs/2309.12608

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