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

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

ICASSP 2021accepted0 citations

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

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

Abstract

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.

BibTeX

@inproceedings{icassp2021_directionalspars,
  title = {Directional Sparse Filtering Using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech Mixtures},
  author = {Karn Watcharasupat and Anh H. T. Nguyen and Ching-Hui Ooi and Andy W. H. Khong},
  booktitle = {ICASSP 2021},
  year = {2021}
}