@inproceedings{Turnbull07agame-based,
  abstract = {Games based on human computation are a valuable tool for collecting semantic information about images. We show how to transfer this idea into the music domain in order to collect high-quality semantic data for songs. We present Listen Game, a online, multiplayer game that measures the semantic relationship between music and words. In the normal mode, a player sees a list of semantically related words (e.g., ‘Instruments’, ‘Emotions ’ ‘Usages’) and is asked to pick the best and worst word to describe a song. In the freestyle mode, a user is asked to suggest a new word that describes the music. Each player receives realtime feedback on the agreement amongst all players. We show that we can use the data collected during a twoweek pilot study of Listen Game to learn a supervised multiclass labeling (SML) model which can annotate a novel song with meaningful words and retrieve relevant songs from a database of audio content.},
  author = {Turnbull, Douglas and Liu, Ruoran and Barrington, Luke and Lanckriet, Gert},
  booktitle = {In 8th International Conference on Music Information Retrieval (ISMIR},
  interhash = {84dbb47780598f72fb33e7e1e431fdb9},
  intrahash = {daa312cc50ee2e53a48fe78f88586a8f},
  title = {A game-based approach for collecting semantic annotations of music},
  year = 2007
}