| Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs SM Kye, Y Jung, HB Lee, SJ Hwang, H Kim Interspeech, 2020 | 62 | 2020 |
| Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network J Bae, J Stocks, A Heywood, Y Jung, L Jenkins, V Hill, A Katsaggelos, ... Neurobiology of aging 99, 53-64, 2021 | 53 | 2021 |
| Fithubert: Going thinner and deeper for knowledge distillation of speech self-supervised learning Y Lee, K Jang, J Goo, Y Jung, H Kim Interspeech 2022, 2022 | 50 | 2022 |
| Improving Multi-Scale Aggregation Using Feature Pyramid Module for Robust Speaker Verification of Variable-Duration Utterances Y Jung, SM Kye, Y Choi, M Jung, H Kim Interspeech, 2020 | 48 | 2020 |
| Joint Learning Using Denoising Variational Autoencoders for Voice Activity Detection Y Jung, Y Kim, Y Choi, H Kim Interspeech, 1210-1214, 2018 | 37 | 2018 |
| Spatial pyramid encoding with convex length normalization for text-independent speaker verification Y Jung, Y Kim, H Lim, Y Choi, H Kim Interspeech, 4030-4034, 2019 | 34 | 2019 |
| Neural MOS Prediction for Synthesized Speech Using Multi-Task Learning With Spoofing Detection and Spoofing Type Classification Y Choi, Y Jung, H Kim 2021 IEEE Spoken Language Technology Workshop (SLT), 2020 | 29 | 2020 |
| Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling Y Choi, Y Jung, H Kim Interspeech, 2020 | 27 | 2020 |
| A unified deep learning framework for short-duration speaker verification in adverse environments Y Jung, Y Choi, H Lim, H Kim IEEE Access 8, 175448-175466, 2020 | 23 | 2020 |
| Linear-scale filterbank for deep neural network-based voice activity detection Y Jung, Y Kim, H Lim, H Kim 2017 20th Conference of the Oriental Chapter of the International …, 2017 | 21 | 2017 |
| Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification Y Jung, Y Choi, H Kim 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019 | 20 | 2019 |
| Development of distant multi-channel speech and noise databases for speech recognition by in-door conversational robots Y Suh, Y Kim, H Lim, J Goo, Y Jung, Y Choi, H Kim, DL Choi, Y Lee 2017 20th Conference of the Oriental Chapter of the International …, 2017 | 20 | 2017 |
| Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification using CTC-based Soft VAD and Global Query Attention M Jung, Y Jung, J Goo, H Kim Interspeech, 2020 | 19 | 2020 |
| Additional Shared Decoder on Siamese Multi-view Encoders for Learning Acoustic Word Embeddings M Jung, H Lim, J Goo, Y Jung, H Kim 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019 | 17 | 2019 |
| Dynamic Noise Embedding: Noise Aware Training and Adaptation for Speech Enhancement J Lee, Y Jung, M Jung, H Kim APSIPA ASC 2020, 2020 | 16 | 2020 |
| Dual Attention in Time and Frequency Domain for Voice Activity Detection J Lee, Y Jung, H Kim Interspeech, 2020 | 13 | 2020 |
| An end-to-end synthesis method for Korean text-to-speech systems Y Choi, Y Jung, Y Kim, Y Suh, H Kim Phonetics and Speech Sciences 10 (1), 39-48, 2018 | 8 | 2018 |
| Learning to maximize speech quality directly using MOS prediction for neural text-to-speech Y Choi, Y Jung, Y Suh, H Kim IEEE Access 10, 52621-52629, 2022 | 7 | 2022 |
| Transfer learning for predicting conversion from mild cognitive impairment to Dementia of Alzheimer’s type based on 3D-convolutional neural network J Bae, J Stocks, A Heywood, Y Jung, L Jenkins, A Katsaggelos, K Popuri, ... bioRxiv, 2019.12. 20.884932, 2019 | 7 | 2019 |
| Learning acoustic word embeddings with phonetically associated triplet network H Lim, Y Kim, Y Jung, M Jung, H Kim arXiv preprint arXiv:1811.02736, 2018 | 5 | 2018 |
Hoirin KimProfessor of Electrical Engineering, KAIST在 kaist.ac.kr 的电子邮件经过验证
