most citedA Unified Deep Learning Framework for Short-Duration Speaker Verification in Adverse Environments

20 citations · 27 across the 3 of their papers we have counts for

collaborators

7 papers

eess.AS202020 cited

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…

eess.AS2020

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…

eess.AS2020

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,…

eess.AS2020

Non-parallel voice conversion based on source-to-target direct mapping

Sunghee Jung, Youngjoo Suh, Yeunju Choi +1

Recent works of utilizing phonetic posteriograms (PPGs) for non-parallel voice conversion have significantly increased the usability of voice conversion since the source and target…

eess.AS2020

Improving Multi-Scale Aggregation Using Feature Pyramid Module for Robust Speaker Verification of Variable-Duration Utterances

Youngmoon Jung, Seong Min Kye, Yeunju Choi +2

Currently, the most widely used approach for speaker verification is the deep speaker embedding learning. In this approach, we obtain a speaker embedding vector by pooling single-s…

eess.AS20197 cited

Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification

Youngmoon Jung, Yeunju Choi, Hoirin Kim

Voice activity detection (VAD), which classifies frames as speech or non-speech, is an important module in many speech applications including speaker verification. In this paper, w…