A Web-Based Game for Collecting Music Metadata

Abstract

We have designed a web-based game, MajorMiner, that makes collecting descriptions of musical excerpts fun, easy, useful, and objective. Participants describe 10 second clips of songs and score points when their descriptions match those of other participants. The rules were designed to encourage players to be thorough and the clip length was chosen to make judgments objective and specific. To analyse the data, we measured the degree to which binary classifiers could be trained to spot popular tags. We also compared the performance of clip classifiers trained with MajorMiner's tag data to those trained with social tag data from a popular website. On the top 25 tags from each source, MajorMiner's tags were classified correctly 67.2% of the time, while the social tags were classified correctly 62.6% of the time.

Acknowledgements

The authors would like to thank Johanna Devaney for her help and Douglas Turnbull, Youngmoo Kim, and Edith Law for information about their games. This work was supported by the Fu Foundation School of Engineering and Applied Science via a Presidential Fellowship, by the Columbia Academic Quality Fund, and by the National Science Foundation (NSF) under Grants IIS-0238301 and IIS-0713334. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Notes

¹The game is available to play at http://www.majorminer.org

² http://www.last.fm/ and http://www.audioscrobbler.com

³We will use bold font to denote tags.

⁴Available at http://www.gwap.com/

⁵ http://www.listengame.org/

⁶Available at http://www.gwap.com/

⁷ http://schubert.ece.drexel.edu/moodswings/