20 citations · 33 across the 5 of their papers we have counts for
9 papers · 2 filters
Learning to Maximize Speech Quality Directly Using MOS Prediction for Neural Text-to-Speech
Yeunju Choi, Youngmoon Jung, Youngjoo Suh +1
Although recent neural text-to-speech (TTS) systems have achieved high-quality speech synthesis, there are cases where a TTS system generates low-quality speech, mainly caused by l…
A Unified Deep Learning Framework for Short-Duration Speaker Verification in Adverse Environments
Youngmoon Jung, Yeunju Choi, Hyungjun Lim +1
Speaker verification (SV) has recently attracted considerable research interest due to the growing popularity of virtual assistants. At the same time, there is an increasing requir…
Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling
Yeunju Choi, Youngmoon Jung, Hoirin Kim
While deep learning has made impressive progress in speech synthesis and voice conversion, the assessment of the synthesized speech is still carried out by human participants. Seve…
Dynamic Noise Embedding: Noise Aware Training and Adaptation for Speech Enhancement
Joohyung Lee, Youngmoon Jung, Myunghun Jung +1
Estimating noise information exactly is crucial for noise aware training in speech applications including speech enhancement (SE) which is our focus in this paper. To estimate nois…
Neural MOS Prediction for Synthesized Speech Using Multi-Task Learning With Spoofing Detection and Spoofing Type Classification
Yeunju Choi, Youngmoon Jung, Hoirin Kim
Several studies have proposed deep-learning-based models to predict the mean opinion score (MOS) of synthesized speech, showing the possibility of replacing human raters. However,…
Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification using CTC-based Soft VAD and Global Query Attention
Myunghun Jung, Youngmoon Jung, Jahyun Goo +1
Keyword spotting (KWS) and speaker verification (SV) have been studied independently although it is known that acoustic and speaker domains are complementary. In this paper, we pro…