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myMoodplay: An interactive mood-based music discovery app

Alo Allik, György Fazekas, Mathieu Barthet, Mark Sandler
myMoodplay is a web app that allows users to interactively discover music by selecting desired emotions. The application uses the Web Audio API, JavaScript animation for visualisation, linked data formats and affective computing technologies. We explore how artificial intelligence, semantic web and audio synthesis can be combined to provide new personalised online musical experiences. Users can choose degrees of energy and pleasantness to shape the desired musical mood trajectory. Semantic Web technologies have been embedded in the system to query mood coordinates from a triple store using a SPARQL endpoint and to connect to external linked data sources for metadata.
            
@inproceedings{2016_51,
  abstract = {myMoodplay is a web app that allows users to interactively discover music by selecting desired emotions. The application uses the Web Audio API, JavaScript animation for visualisation, linked data formats and affective computing technologies. We explore how artificial intelligence, semantic web and audio synthesis can be combined to provide new personalised online musical experiences. Users can choose degrees of energy and pleasantness to shape the desired musical mood trajectory. Semantic Web technologies have been embedded in the system to query mood coordinates from a triple store using a SPARQL endpoint and to connect to external linked data sources for metadata.},
  address = {Atlanta, Georgia},
  author = {Allik, Alo and Fazekas, György and Barthet, Mathieu and Sandler, Mark},
  booktitle = {Proceedings of the International Web Audio Conference},
  editor = {Freeman, Jason and Lerch, Alexander and Paradis, Matthew},
  month = {April},
  pages = {},
  publisher = {Georgia Tech},
  series = {WAC '16},
  title = {myMoodplay: An interactive mood-based music discovery app},
  year = {2016},
  ISSN = {2663-5844}
}