13 citations · 23 across the 9 of their papers we have counts for
6 papers · 1 filter
Audio Generation with Multiple Conditional Diffusion Model
Zhifang Guo, Jianguo Mao, Rui Tao +4
Text-based audio generation models have limitations as they cannot encompass all the information in audio, leading to restricted controllability when relying solely on text. To add…
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4
Yiming Li, Zhifang Guo, Zhirong Ye +6
In this paper, we describe in detail our system for DCASE 2022 Task4. The system combines two considerably different models: an end-to-end Sound Event Detection Transformer (SEDT)…
Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
Zhirong Ye, Xiangdong Wang, Hong Liu +4
Sound event detection (SED) has gained increasing attention with its wide application in surveillance, video indexing, etc. Existing models in SED mainly generate frame-level predi…
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…