7 papers
TD3Net: A temporal densely connected multi-dilated convolutional network for lipreading
Byung Hoon Lee, Wooseok Shin, Sung Won Han
The word-level lipreading approach typically employs a two-stage framework with separate frontend and backend architectures to model dynamic lip movements. Each component has been…
PrevMatch: Revisiting and Maximizing Temporal Knowledge in Semi-Supervised Semantic Segmentation
Wooseok Shin, Hyun Joon Park, Jin Sob Kim +3
In semi-supervised semantic segmentation, the Mean Teacher- and co-training-based approaches are employed to mitigate confirmation bias and coupling problems. However, despite thei…
A Robust framework for sound event localization and detection on real recordings
Jin Sob Kim, Hyun Joon Park, Wooseok Shin +1
This technical report describes the systems submitted to the DCASE2022 challenge task 3: sound event localization and detection (SELD). The task aims to detect occurrences of sound…
Rethinking Leveraging Pre-Trained Multi-Layer Representations for Speaker Verification
Jin Sob Kim, Hyun Joon Park, Wooseok Shin +1
Recent speaker verification studies have achieved notable success by leveraging layer-wise output from pre-trained Transformer models. However, few have explored the advancements i…
Layer-aware TDNN: Speaker Recognition Using Multi-Layer Features from Pre-Trained Models
Jin Sob Kim, Hyun Joon Park, Wooseok Shin +2
Recent advances in self-supervised learning (SSL) on Transformers have significantly improved speaker verification (SV) by providing domain-general speech representations. However,…
Leveraging Out-of-Distribution Unlabeled Images: Semi-Supervised Semantic Segmentation with an Open-Vocabulary Model
Wooseok Shin, Jisu Kang, Hyeonki Jeong +2
In semi-supervised semantic segmentation, existing studies have shown promising results in academic settings with controlled splits of benchmark datasets. However, the potential be…