metadata

pretty_name: DataSynthSELD
size_categories:
  - 100B<n<1T
task_categories:
  - audio-classification

PSELDNets: Pre-trained Neural Networks on Large-scale Synthetic Datasets for Sound Event Localization and Detection

Paper
GitHub

This repo contains 67,000 1-minute clips amounting to approximately 1,117 hours for training, and 3,060 1-minute clips amounting to roughly 51 hours for testing.
These datasets features an ontology of 170 sound classes and are generated by convolving sound event clips from FSD50K with simulated SRIRs (for training) or collected SRIRs from TAU-SRIR DB (for testing).
The datasets are generated by this tools.

Download

Synthetic Datasets
Pre-trained checkpoints

Citation

Please cite our papers as below if you use the datasets, codes and models of PSELDNets.

[1] Jinbo Hu, Yin Cao, Ming Wu, Fang Kang, Feiran Yang, Wenwu Wang, Mark D. Plumbley, Jun Yang, "PSELDNets: Pre-trained Neural Networks on Large-scale Synthetic Datasets for Sound Event Localization and Detection" arXiv:2411.06399, 2024. URL