6 citations · 12 across the 4 of their papers we have counts for
4 papers
SP-SEDT: Self-supervised Pre-training for Sound Event Detection Transformer
Zhirong Ye, Xiangdong Wang, Hong Liu +4
Recently, an event-based end-to-end model (SEDT) has been proposed for sound event detection (SED) and achieves competitive performance. However, compared with the frame-based mode…
Learning generic feature representation with synthetic data for weakly-supervised sound event detection by inter-frame distance loss
Yuxin Huang, Liwei Lin, Xiangdong Wang +4
Due to the limitation of strong-labeled sound event detection data set, using synthetic data to improve the sound event detection system performance has been a new research focus.…
Guided multi-branch learning systems for sound event detection with sound separation
Yuxin Huang, Liwei Lin, Shuo Ma +5
In this paper, we describe in detail our systems for DCASE 2020 Task 4. The systems are based on the 1st-place system of DCASE 2019 Task 4, which adopts weakly-supervised framework…
Guided Learning Convolution System for DCASE 2019 Task 4
Liwei Lin, Xiangdong Wang, Hong Liu +1
In this paper, we describe in detail the system we submitted to DCASE2019 task 4: sound event detection (SED) in domestic environments. We employ a convolutional neural network (CN…