19 citations · 43 across the 12 of their papers we have counts for
4 papers · 1 filter
ESPnet-SE++: Speech Enhancement for Robust Speech Recognition, Translation, and Understanding
Yen-Ju Lu, Xuankai Chang, Chenda Li +10
This paper presents recent progress on integrating speech separation and enhancement (SSE) into the ESPnet toolkit. Compared with the previous ESPnet-SE work, numerous features hav…
Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
Yen-Ju Lu, Samuele Cornell, Xuankai Chang +5
This paper describes our submission to the L3DAS22 Challenge Task 1, which consists of speech enhancement with 3D Ambisonic microphones. The core of our approach combines Deep Neur…
Conditional Diffusion Probabilistic Model for Speech Enhancement
Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe +3
Speech enhancement is a critical component of many user-oriented audio applications, yet current systems still suffer from distorted and unnatural outputs. While generative models…
Discretization and Re-synthesis: an alternative method to solve the Cocktail Party Problem
Jing Shi, Xuankai Chang, Tomoki Hayashi +3
Deep learning based models have significantly improved the performance of speech separation with input mixtures like the cocktail party. Prominent methods (e.g., frequency-domain a…