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--- |
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pretty_name: DataSynthSELD |
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size_categories: |
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- 100B<n<1T |
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task_categories: |
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- audio-classification |
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--- |
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# PSELDNets: Pre-trained Neural Networks on Large-scale Synthetic Datasets for Sound Event Localization and Detection |
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- [Paper](https://arxiv.org/abs/2411.06399) |
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- [GitHub](https://github.com/Jinbo-Hu/PSELDNets) |
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1. 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. |
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2. These datasets features an ontology of 170 sound classes and are generated by convolving sound event clips from [FSD50K](https://zenodo.org/records/4060432) with simulated SRIRs (for training) or collected SRIRs from [TAU-SRIR DB](https://zenodo.org/records/6408611) (for testing). |
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3. The datasets are generated by this [tools](https://github.com/Jinbo-Hu/SELD-Data-Generator). |
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## Download |
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- [Synthetic Datasets](https://huggingface.co/datasets/Jinbo-HU/PSELDNets/tree/main/dataset) |
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- [Pre-trained checkpoints](https://huggingface.co/datasets/Jinbo-HU/PSELDNets/tree/main/model) |
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## Citation |
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Please cite our papers as below if you use the datasets, codes and models of PSELDNets. |
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[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](https://arxiv.org/abs/2411.06399), 2024. [URL](https://arxiv.org/abs/2411.06399) |
