16 citations · 31 across the 19 of their papers we have counts for
25 papers
Self-supervised Complex Network for Machine Sound Anomaly Detection
Miseul Kim, Minh Tri Ho, Hong-Goo Kang
In this paper, we propose an anomaly detection algorithm for machine sounds with a deep complex network trained by self-supervision. Using the fact that phase continuity informatio…
Style Modeling for Multi-Speaker Articulation-to-Speech
Miseul Kim, Zhenyu Piao, Jihyun Lee +1
In this paper, we propose a neural articulation-to-speech (ATS) framework that synthesizes high-quality speech from articulatory signal in a multi-speaker situation. Most conventio…
Pruning Self-Attention for Zero-Shot Multi-Speaker Text-to-Speech
Hyungchan Yoon, Changhwan Kim, Eunwoo Song +2
For personalized speech generation, a neural text-to-speech (TTS) model must be successfully implemented with limited data from a target speaker. To this end, the baseline TTS mode…
Feature Normalization for Fine-tuning Self-Supervised Models in Speech Enhancement
Hejung Yang, Hong-Goo Kang
Large, pre-trained representation models trained using self-supervised learning have gained popularity in various fields of machine learning because they are able to extract high-q…
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…