1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
MF-PAM: Accurate Pitch Estimation through Periodicity Analysis and Multi-level Feature Fusion
Woo-Jin Chung, Doyeon Kim, Soo-Whan Chung +1
We introduce Multi-level feature Fusion-based Periodicity Analysis Model (MF-PAM), a novel deep learning-based pitch estimation model that accurately estimates pitch trajectory in…
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…
Phase Continuity: Learning Derivatives of Phase Spectrum for Speech Enhancement
Doyeon Kim, Hyewon Han, Hyeon-Kyeong Shin +2
Modern neural speech enhancement models usually include various forms of phase information in their training loss terms, either explicitly or implicitly. However, these loss terms…