ISMIR 2008 – Session 2c – Knowledge Representation, Tags, Metadata MOODSWINGS: A COLLABORATIVE GAME FORMUSIC MOOD LABEL COLLECTION

There are many problems in the field of music infor-mation retrieval that are not only difficult for machines to solve, but that do not have well-defined answers. In labeling and detecting emotions within music, this lack of specificity makes it difficult to train systems that rely on quantified la-bels for supervised machine learning. The collection of such “ground truth ” data for these subjectively perceived features necessarily requires human subjects. Traditional methods of data collection, such as the hiring of subjects, can be flawed, since labeling tasks are time-consuming, tedious, and expensive. Recently, there have been many initiatives to use customized online games to harness so-called “Human Computation ” for the collection of label data, and several such games have been proposed to collect labels spanning an excerpt of music. We present a new game, MoodSwing