Info hash | fecaeaf2f97a0cd9f62fdaafaac70a6a96fa4ac0 |
Last mirror activity | 1:11 ago |
Size | 214.16GB (214,163,931,939 bytes) |
Added | 2024-08-23 17:36:41 |
Views | 42 |
Hits | 188 |
ID | 5194 |
Type | multi |
Downloaded | 100 time(s) |
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Folder | msd_targz |
Num files | 28 files [See full list] |
Mirrors | 5 complete, 1 downloading = 6 mirror(s) total [Log in to see full list] |

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Type: Dataset
Tags: Dataset, Features, metadata, million, song, music
Bibtex:
Tags: Dataset, Features, metadata, million, song, music
Bibtex:
@inproceedings{thierry_bertin_mahieux_2018_1415820, author= {Thierry Bertin-Mahieux and Daniel P. W. Ellis and Brian Whitman and Paul Lamere}, title= {The Million Song Dataset.}, booktitle= {{Proceedings of the 12th International Society for Music Information Retrieval Conference}}, year= {2018}, pages= {591-596}, publisher= {ISMIR}, month= {sep}, venue= {Miami, United States}, doi= {10.5281/zenodo.1415820}, url= {https://doi.org/10.5281/zenodo.1415820}, abstract= {We introduce the Million Song Dataset, a freely-available collection of audio features and metadata for a million con- temporary popular music tracks. We describe its creation process, its content, and its possible uses. Attractive fea- tures of the Million Song Database include the range of ex- isting resources to which it is linked, and the fact that it is the largest current research dataset in our field. As an illustra- tion, we present year prediction as an example application, a task that has, until now, been difficult to study owing to the absence of a large set of suitable data. We show positive results on year prediction, and discuss more generally the future development of the dataset.}, keywords= {million, song, dataset, music, features, metadata}, terms= {}, license= {}, superseded= {} }