arXiv:2211.08872
공식 코드 · Papers with Code
McNet: Fuse Multiple Cues for Multichannel Speech Enhancement
원문 초록
In multichannel speech enhancement, both spectral and spatial information are vital for discriminating between speech and noise. How to fully exploit these two types of information and their temporal dynamics remains an interesting research problem. As a solution to this problem, this paper proposes a multi-cue fusion network named McNet, which cascades four modules to respectively exploit the full-band spatial, narrow-band spatial, sub-band spectral, and full-band spectral information. Experiments show that each module in the proposed network has its unique contribution and, as a whole, notably outperforms other state-of-the-art methods.
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Efficient Speech Enhancement via Embeddings from Pre-trained Generative Audioencoders
Lessons Learned from the URGENT 2024 Speech Enhancement Challenge
FlowSE: Efficient and High-Quality Speech Enhancement via Flow Matching
Training-Free Multi-Step Audio Source Separation
토론
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