3 accepted papers
Diffusion-based generative models have been shown to be highly effective in various speech enhancement tasks. This work presents an analysis of a flow matching-based framework for generative speech enhancement as a simpler alternative to diffusion. Four different modifications to flow matching are p…
In this work, we investigate application of generative speech enhancement to improve the robustness of ASR models in noisy and reverberant conditions. We employ a recently-proposed speech enhancement model based on Schrödinger bridge, which has been shown to perform well compared to diffusion-based…
Optimization of modern ASR architectures is among the highest priority tasks since it saves many computational resources for model training and inference. The work proposes a new Uconv-Conformer architecture <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlin…