activity
20222024
most citedAn empirical study on speech restoration guided by self supervised speech representation

4 citations · 7 across the 6 of their papers we have counts for

collaborators

5 papers

eess.AS20231 cited

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…

eess.AS20234 cited

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…

eess.AS2023

MoLE : Mixture of Language Experts for Multi-Lingual Automatic Speech Recognition

Yoohwan Kwon, Soo-Whan Chung

Multi-lingual speech recognition aims to distinguish linguistic expressions in different languages and integrate acoustic processing simultaneously. In contrast, current multi-ling…

cs.LG20232 cited

Imaginary Voice: Face-styled Diffusion Model for Text-to-Speech

Jiyoung Lee, Joon Son Chung, Soo-Whan Chung

The goal of this work is zero-shot text-to-speech synthesis, with speaking styles and voices learnt from facial characteristics. Inspired by the natural fact that people can imagin…

eess.AS2022

Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting

Hyeon-Kyeong Shin, Hyewon Han, Doyeon Kim +2

In this paper, we propose a novel end-to-end user-defined keyword spotting method that utilizes linguistically corresponding patterns between speech and text sequences. Unlike prev…