DocumentCode :
3318565
Title :
Evaluating music emotion recognition: Lessons from music genre recognition?
Author :
Sturm, Bob L.
Author_Institution :
Audio Anal. Lab., Aalborg Univ. Copenhagen, Aalborg, Denmark
fYear :
2013
fDate :
15-19 July 2013
Firstpage :
1
Lastpage :
6
Abstract :
A fundamental problem with nearly all work in music genre recognition (MGR) is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations.
Keywords :
emotion recognition; learning (artificial intelligence); music; MER; MGR; music emotion recognition; music genre recognition; Accuracy; Computer crashes; Emotion recognition; Lightning; Multiple signal classification; Music; Training; Evaluation; machine learning; music emotion recognition; music genre recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo Workshops (ICMEW), 2013 IEEE International Conference on
Conference_Location :
San Jose, CA
Type :
conf
DOI :
10.1109/ICMEW.2013.6618342
Filename :
6618342
Link To Document :
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