Exploring the importance of individual differences to the automatic estimation of emotions induced by music. Sagha, H., Coutinho, E., & Schuller, B. In AVEC 2015 - Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge, co-Located with MM 2015, pages 57-63, 10, 2015. ACM Press.
Exploring the importance of individual differences to the automatic estimation of emotions induced by music [link]Website  doi  abstract   bibtex   
The goal of this study was to evaluate the impact of the inclusion of listener-related factors (individual differences) on the prediction of music induced affect. A group of 24 subjects listened to a set of music excerpts previously demonstrated to express specific emotional characteristics (in terms of Arousal and Valence), and we collected information related to listeners' stable (personality, emotional intelligence, attentiveness, music preferences) and transient (mood, and physiological activity) states. Through a series of regression analysis we identified those factors which have a significant explanatory power over the affective states induced in the listeners. Our results show that incorporating information related to individual differences permits to identify more accurately the affective states induced in the listeners, which differ from those expressed by the music.
@inproceedings{
 title = {Exploring the importance of individual differences to the automatic estimation of emotions induced by music},
 type = {inproceedings},
 year = {2015},
 keywords = {abstract,conference},
 pages = {57-63},
 websites = {http://dl.acm.org/citation.cfm?doid=2808196.2811643},
 month = {10},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {497e5bf2-b45b-3385-bf8f-85674f8d836e},
 created = {2020-05-29T11:51:38.946Z},
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 abstract = {The goal of this study was to evaluate the impact of the inclusion of listener-related factors (individual differences) on the prediction of music induced affect. A group of 24 subjects listened to a set of music excerpts previously demonstrated to express specific emotional characteristics (in terms of Arousal and Valence), and we collected information related to listeners' stable (personality, emotional intelligence, attentiveness, music preferences) and transient (mood, and physiological activity) states. Through a series of regression analysis we identified those factors which have a significant explanatory power over the affective states induced in the listeners. Our results show that incorporating information related to individual differences permits to identify more accurately the affective states induced in the listeners, which differ from those expressed by the music.},
 bibtype = {inproceedings},
 author = {Sagha, Hesam and Coutinho, Eduardo and Schuller, Björn},
 doi = {10.1145/2808196.2811643},
 booktitle = {AVEC 2015 - Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge, co-Located with MM 2015}
}

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