Contextual Tags for music auto-tagging

<p>The dataset is composed of 15 contextual tags extracted based on user&#39;s usage through created playlists in the Deezer catalog. The tags are: &quot; car, chill, club, dance, gym, happy, night, party, relax, running, sad, sleep, summer, work, workout&quot;. For each&nbsp; track one or multiple tags are associated with it indicating that users listen to the track in the associated context.&nbsp;</p> <p>The creation of the dataset and the initial baseline of an auto-tagging model is described in the paper: Ibrahim, Karim M.,&nbsp;Jimena&nbsp;Royo-Letelier,&nbsp;Elena V. Epure, Geoffroy Peeters,&nbsp;and Ga&euml;l Richard. &quot;AUDIO-BASED AUTO-TAGGING WITH CONTEXTUAL TAGS FOR MUSIC.&quot;&nbsp;<em>2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</em>. IEEE, 2020.</p> <p>The dataset is composed of the SONG_ID&nbsp;which is the ID of the track in the Deezer catalog. Each track is labeled with each tag as either 1 (indicating a track&#39;s&nbsp;presence in the context) or 0 (indicating a track&#39;s absence). The 30 seconds track previews used to train the model in the paper can be accessed through the Deezer API:&nbsp;<a href="https://developers.deezer.com/api">https://developers.deezer.com/api</a>&nbsp;</p> <p>.</p>