TY - GEN
T1 - Exploring mood metadata
T2 - 8th International Conference on Music Information Retrieval, ISMIR 2007
AU - Hu, Xiao
AU - Downie, J. Stephen
PY - 2007/12/1
Y1 - 2007/12/1
N2 - There is a growing interest in developing and then evaluating Music Information Retrieval (MIR) systems that can provide automated access to the mood dimension of music. Mood as a music access feature, however, is not well understood in that the terms used to describe it are not standardized and their application can be highly idiosyncratic. To better understand how we might develop methods for comprehensively developing and formally evaluating useful automated mood access techniques, we explore the relationships that mood has with genre, artist and usage metadata. Statistical analyses of term interactions across three metadata collections (AllMusicGuide.com, epinions.com and Last.fm) reveal important consistencies within the genre-mood and artist-mood relationships. These consistencies lead us to recommend a cluster-based approach that overcomes specific term-related problems by creating a relatively small set of data-derived "mood spaces" that could form the ground-truth for a proposed MIREX "Automated Mood Classification" task.
AB - There is a growing interest in developing and then evaluating Music Information Retrieval (MIR) systems that can provide automated access to the mood dimension of music. Mood as a music access feature, however, is not well understood in that the terms used to describe it are not standardized and their application can be highly idiosyncratic. To better understand how we might develop methods for comprehensively developing and formally evaluating useful automated mood access techniques, we explore the relationships that mood has with genre, artist and usage metadata. Statistical analyses of term interactions across three metadata collections (AllMusicGuide.com, epinions.com and Last.fm) reveal important consistencies within the genre-mood and artist-mood relationships. These consistencies lead us to recommend a cluster-based approach that overcomes specific term-related problems by creating a relatively small set of data-derived "mood spaces" that could form the ground-truth for a proposed MIREX "Automated Mood Classification" task.
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M3 - Conference contribution
AN - SCOPUS:84873596722
SN - 9783854032182
T3 - Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007
SP - 67
EP - 72
BT - Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007
Y2 - 23 September 2007 through 27 September 2007
ER -