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Hit Song Prediction Dataset
\n\nThis dataset is based on the Million Song Dataset (MSD), which contains one million songs that are representative for western commercial music released between 1922 and 2011. The dataset contains release year information for 515,576 of the MSD songs. Please refer to http://millionsongdataset.com/ for further information on the million song dataset.
\n\nFor our hit song prediction experiments, we extract high- and low-level audio features using the Essentia toolkit (cf. https://essentia.upf.edu/). For the high-level features, we make use of the pre-trained classifiers as provided by Essentia. For a detailed description of the features, please visit the Essentia documentation.
\n\n
\nThe dataset hence contains:
\nIf you make use of the dataset, please kindly cite the following paper:
Eva Zangerle, Michael Vötter, Ramona Huber, and Yi-Hsuan Yang. Hit Song Prediction: Leveraging Low- and High-Level Audio Features. In Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019), 2019.
\n\n
\n@inproceedings{zangerle_ismir19,
\ntitle = {{Hit Song Prediction: Leveraging Low- and High-Level Audio Features}},
\nauthor = {Eva Zangerle and Ramona Huber and Michael V\\"{o}tter and Yi-Hsuan Yang},
\nyear = {2019},
\nbooktitle = {{Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019)}},
\n}