MoodSwings: A Collaborative Game for Music Mood Label Collection

@inproceedings{Kim2008MoodSwingsAC,
  title={MoodSwings: A Collaborative Game for Music Mood Label Collection},
  author={Youngmoo E. Kim and Erik M. Schmidt and Lloyd Emelle},
  booktitle={ISMIR},
  year={2008}
}
There are many problems in the field of music information 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 labels 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… CONTINUE READING
Highly Cited
This paper has 119 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 73 extracted citations

Review of data features-based music emotion recognition methods

Multimedia Systems • 2017
View 5 Excerpts
Highly Influenced

User-centered design of a social game to tag music

KDD Workshop on Human Computation • 2009
View 4 Excerpts
Highly Influenced

120 Citations

01020'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 120 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…