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#diffusion models Open access Oct 2026

Deep learning-driven joint blind source separation and noise suppression for audio signals: a performance optimization study

Separating overlapping talkers and suppressing non-stationary noise are coupled problems, yet conventional pipelines solve them in isolation, so separation artifacts propagate untouched into the denoising stage. We therefore build a time–frequency joint separation–denoising network: a learnable encoder, a multi-scale...

Rong-Wen Xie, Zeng-Jie Tao, Lin Lei et al. · 0 citations
Preprint Aug 2026

A Fast and Scalable Transformer Pipeline for Binary Black Hole Detection

With the projected increase in the detection rate of compact-binary coalescences in the coming decade, there is critical need to develop fast, robust, and scalable alternatives to matched filtering for gravitational-wave searches. Transformer models have revolutionized natural language and audio processing but their ap...

Chayan Chatterjee, Abigail Petulante, Haowei Fu et al. · 0 citations

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