Predicting spotify audio features from Last.fm tags

Author:

Castillo Jaime Ramírez,Flores M. JuliaORCID,Leray Philippe

Funder

Junta de Comunidades de Castilla-La Mancha

Universidad de Castilla-La Mancha

Ministerio de Ciencia e Innovación

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference15 articles.

1. Ramirez J, Flores MJ (2020) Machine learning for music genre: multifaceted review and experimentation with audioset. J Intell Inf Syst 55(3):469–499. https://doi.org/10.1007/s10844-019-00582-9

2. Laurier C, Sordo M, Serra J, Herrera P (2009) Music mood representations from social tags. In: Proceedings of the 10th international society for music information retrieval conference (ISMIR), pp 381–386

3. Çano E, Morisio M (2017) Music mood dataset creation based on last.fm tags. In: Proceedings of the 4th international conference on artificial intelligence and applications, pp 15–26. https://doi.org/10.5121/csit.2017.70603

4. Bodó Z, Szilágyi E (2018) Connecting the last. fm dataset to lyricwiki and musicbrainz. lyrics-based experiments in genre classification. Acta Univ Sapientiae, Inform 10(2):158–182

5. Bertin-Mahieux T, Ellis DPW, Whitman B, Lamere P (2011) The million song dataset. In: Proceedings of the 12th international conference on music information retrieval (ISMIR), pp 591–596

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