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Update README.md
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README.md
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@@ -79,6 +79,13 @@ dataset = datasets.load_dataset("jpdiazpardo/scream_detection_heavy_metal")
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### Youtube playlist
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[Scream Detection Dataset](https://www.youtube.com/playlist?list=PLnkRJFUtBDzWOEnVOiWTVxGOWD70LDwtC)
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### Licensing Information
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MIT License
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year={2022},
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volume={abs/2205.05580}
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}
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```
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### Youtube playlist
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[Scream Detection Dataset](https://www.youtube.com/playlist?list=PLnkRJFUtBDzWOEnVOiWTVxGOWD70LDwtC)
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### Source Data
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#### Initial Data Collection and Normalization
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The data was collected from the YouTube playlist above and trimmed using the timestamps provided in the dataset.
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The audio files were passed through the [Spleeter](https://joss.theoj.org/papers/10.21105/joss.02154) (Hennequin et al., 2020) source separation algorithm to separate the vocals from the other components.
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### Licensing Information
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MIT License
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year={2022},
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volume={abs/2205.05580}
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}
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@article{Hennequin2020,
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doi = {10.21105/joss.02154},
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url = {https://doi.org/10.21105/joss.02154},
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year = {2020}, publisher = {The Open Journal},
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volume = {5}, number = {50}, pages = {2154},
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author = {Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
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title = {Spleeter: a fast and efficient music source separation tool with pre-trained models},
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journal = {Journal of Open Source Software}
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}
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```
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