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DCASE 2024 Task 9: Language-Queried Audio Source Separation | Pre-trained Weights for the Baseline System

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NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/10887459
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== Descriptions == We trained the AudioSep [1] model using the development set (Clotho and augmented FSD50K datasets) for 200k steps with a batch size of 16 using one Nvidia A100 GPU (around 1 day). Model details can be found in the AudioSep paper. Pre-trained weights for the baseline system: audiosep_16k,baseline,step=200000.ckpt Baseline codebase: GitHub: https://github.com/Audio-AGI/dcase2024_task9_baseline == Reference == [1] Liu X, Kong Q, Zhao Y, et al. Separate anything you describe. arXiv:2308.05037, 2023. == Contact == Xubo Liu, xubo.liu@surrey.ac.uk
创建时间:
2024-03-27
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