Abstract : In this paper, we decided to study the effect of extracted audio features, using the analysis tool Essentia, on the quality of constructed music emotion detection classifiers. The research process included constructing training data, feature extraction, feature selection, and building classifiers. We selected features and found sets of features that were the most useful for detecting individual emotions. We examined the effect of low-level, rhythm and tonal features on the accuracy of the constructed classifiers. We built classifiers for different combinations of feature sets, which enabled distinguishing the most useful feature sets for individual emotions.
https://hal.inria.fr/hal-01444499 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, January 24, 2017 - 10:41:42 AM Last modification on : Wednesday, January 25, 2017 - 1:04:03 AM Long-term archiving on: : Tuesday, April 25, 2017 - 6:22:13 PM
Jacek Grekow. Audio Features Dedicated to the Detection of Four Basic Emotions. 14th Computer Information Systems and Industrial Management (CISIM), Sep 2015, Warsaw, Poland. pp.583-591, ⟨10.1007/978-3-319-24369-6_49⟩. ⟨hal-01444499⟩