Journal of New Music Research
The journal version of lat year’s ISMIR paper is ready to be published. The main addition is an analysis of the tags we’ve collected with the game, including a comparison with tags for the same music from Last.fm. In these experiments, we compared the accuracy of classifiers trained on different tag corpora, which was a bit tricky. Since the Last.fm tags and the MajorMiner tags were not the same, we could only compare seven of them directly. For an overall comparison, we used the mean accuracy across tags, which is useful, but not terribly sophisticated. Here’s the 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 analyze 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.