5 citations · 5 across the 5 of their papers we have counts for
5 papers
HuBERT-VIC: Improving Noise-Robust Automatic Speech Recognition of Speech Foundation Model via Variance-Invariance-Covariance Regularization
Hyebin Ahn, Kangwook Jang, Hoirin Kim
Noise robustness in speech foundation models (SFMs) has been a critical challenge, as most models are primarily trained on clean data and experience performance degradation when th…
ParaNoise-SV: Integrated Approach for Noise-Robust Speaker Verification with Parallel Joint Learning of Speech Enhancement and Noise Extraction
Minu Kim, Kangwook Jang, Hoirin Kim
Noise-robust speaker verification leverages joint learning of speech enhancement (SE) and speaker verification (SV) to improve robustness. However, prevailing approaches rely on im…
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
Sungnyun Kim, Sungwoo Cho, Sangmin Bae +2
Audio-visual speech recognition (AVSR) incorporates auditory and visual modalities to improve recognition accuracy, particularly in noisy environments where audio-only speech syste…
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake Detection
Hyun Myung Kim, Kangwook Jang, Hoirin Kim
As speech synthesis systems continue to make remarkable advances in recent years, the importance of robust deepfake detection systems that perform well in unseen systems has grown.…
FitHuBERT: Going Thinner and Deeper for Knowledge Distillation of Speech Self-Supervised Learning
Yeonghyeon Lee, Kangwook Jang, Jahyun Goo +2
Large-scale speech self-supervised learning (SSL) has emerged to the main field of speech processing, however, the problem of computational cost arising from its vast size makes a…