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eess.AS2022★ 1 cited
Self-Remixing: Unsupervised Speech Separation via Separation and Remixing
Kohei Saijo, Tetsuji Ogawa
We present Self-Remixing, a novel self-supervised speech separation method, which refines a pre-trained separation model in an unsupervised manner. The proposed method consists of…
eess.AS2022
Spatial Loss for Unsupervised Multi-channel Source Separation
Kohei Saijo, Robin Scheibler
We propose a spatial loss for unsupervised multi-channel source separation. The proposed loss exploits the duality of direction of arrival (DOA) and beamforming: the steering and b…
eess.AS2022
Remix-cycle-consistent Learning on Adversarially Learned Separator for Accurate and Stable Unsupervised Speech Separation
Kohei Saijo, Tetsuji Ogawa
A new learning algorithm for speech separation networks is designed to explicitly reduce residual noise and artifacts in the separated signal in an unsupervised manner. Generative…