We take the average and covariance over all 'segments', each segmentīeing described by a 12-dimensional timbre vector. The first value is the year (target), ranging from 1922 to 2011.įeatures extracted from the 'timbre' features from The Echo Nest API. It avoids the 'producer effect' by making sure no songįrom a given artist ends up in both the train and test set.ĩ0 attributes, 12 = timbre average, 78 = timbre covariance The songs are rep-resentative of recent western commercial music. The MSD contains metadata and audio analysis for a million songs that were legally available to The Echo Nest. The Million Song Dataset (MSD) is our attempt to help researchers by providing a large-scale dataset. You should respect the following train / test split: tions such as using songs released under Creative Commons (Magnatagatune 9). This data is a subset of the Million Song Dataset:Ī collaboration between LabROSA (Columbia University) and The Echo Nest. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s. Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: Prediction of the release year of a song from audio features. Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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