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RESEARCH PRODUCT
Filtering of Spontaneous and Low Intensity Emotions in Educational Contexts
Mar SaneiroSergio Salmeron-majadasRaúl CabestreroMiguel Arevalillo-herráezJesus G. BoticarioPilar QuirósOlga C. SantosDavid Arnausubject
DiscretizationPoint (typography)Binary classificationComputer scienceSpeech recognitionClassifier (linguistics)Binary numberFilter (signal processing)Affective computingAffect (psychology)description
Affect detection is a challenging problem, even more in educational contexts, where emotions are spontaneous and usually subtle. In this paper, we propose a two-stage detection approach based on an initial binary discretization followed by a specific emotion prediction stage. The binary classification method uses several distinct sources of information to detect and filter relevant time slots from an affective point of view. An accuracy close to 75% at detecting whether the learner has felt an educationally relevant emotion on 20 second time slots has been obtained. These slots can then be further analyzed by a second classifier, to determine the specific user emotion.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-01-01 |