arXiv 2102.001962021-02eess.AScs.LGcs.SDeess.SP

Directional Sparse Filtering using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech Mixtures

Nanyang Technological University（南洋理工大学）；Delta-NTU Corporate Lab for Cyber-Physical Systems（Delta-南大网络物理系统联合实验室）；Delta Electronics Inc（台达电子公司）

Karn Watcharasupat, Anh H. T. Nguyen, Ching-Hui Ooi, Andy W. H. Khong

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发表信息：: Proceedings of the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 4485-4489
DOI：: 10.1109/ICASSP39728.2021.9414336

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英文摘要：

In blind source separation of speech signals, the inherent imbalance in the source spectrum poses a challenge for methods that rely on single-source dominance for the estimation of the mixing matrix. We propose an algorithm based on the directional sparse filtering (DSF) framework that utilizes the Lehmer mean with learnable weights to adaptively account for source imbalance. Performance evaluation in multiple real acoustic environments show improvements in source separation compared to the baseline methods.

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