4 citations · 7 across the 5 of their papers we have counts for
5 papers · 1 filter
Speak in the Scene: Diffusion-based Acoustic Scene Transfer toward Immersive Speech Generation
Miseul Kim, Soo-Whan Chung, Youna Ji +2
This paper introduces a novel task in generative speech processing, Acoustic Scene Transfer (AST), which aims to transfer acoustic scenes of speech signals to diverse environments.…
HD-DEMUCS: General Speech Restoration with Heterogeneous Decoders
Doyeon Kim, Soo-Whan Chung, Hyewon Han +2
This paper introduces an end-to-end neural speech restoration model, HD-DEMUCS, demonstrating efficacy across multiple distortion environments. Unlike conventional approaches that…
An empirical study on speech restoration guided by self supervised speech representation
Jaeuk Byun, Youna Ji, Soo Whan Chung +2
Enhancing speech quality is an indispensable yet difficult task as it is often complicated by a range of degradation factors. In addition to additive noise, reverberation, clipping…
Diffusion-based Generative Speech Source Separation
Robin Scheibler, Youna Ji, Soo-Whan Chung +3
We propose DiffSep, a new single channel source separation method based on score-matching of a stochastic differential equation (SDE). We craft a tailored continuous time diffusion…
Orthonormal Embedding-based Deep Clustering for Single-channel Speech Separation
Soyeon Choe, Soo-Whan Chung, Youna Ji +1
Deep clustering is a deep neural network-based speech separation algorithm that first trains the mixed component of signals with high-dimensional embeddings, and then uses a cluste…