2 citations · 3 across the 4 of their papers we have counts for
4 papers
Rethinking Training Targets, Architectures and Data Quality for Universal Speech Enhancement
Szu-Wei Fu, Rong Chao, Xuesong Yang +6
Universal Speech Enhancement (USE) aims to restore speech quality under diverse degradation conditions while preserving signal fidelity. Despite recent progress, key challenges in…
Robust Speech Recognition with Schrödinger Bridge-Based Speech Enhancement
Rauf Nasretdinov, Roman Korostik, Ante Jukić
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…
Universal Speech Enhancement with Regression and Generative Mamba
Rong Chao, Rauf Nasretdinov, Yu-Chiang Frank Wang +3
The Interspeech 2025 URGENT Challenge aimed to advance universal, robust, and generalizable speech enhancement by unifying speech enhancement tasks across a wide variety of conditi…
Uconv-Conformer: High Reduction of Input Sequence Length for End-to-End Speech Recognition
Andrei Andrusenko, Rauf Nasretdinov, Aleksei Romanenko
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 U…