A hybrid approach for emotion detection in support of affective interaction
Date Issued
2014-12-14
Author(s)
Koroveshovski, Kiril
Chavdarova, Tatjana
Abstract
Affective interaction is a new emerging area of
interest for interaction designers. This research explores the
potential of our hybrid approach that relies on both, lexical and
machine learning techniques for detection of Ekman’s six
emotional categories in user’s text. The initial results of the
performance evaluation of the proposed hybrid approach are
encouraging and comparable to related research. A
demonstrative mobile application that employs the proposed
approach was developed to engage the users in a dialogue that
solicits their reflections on various daily events and provides
appropriate affective responses.
interest for interaction designers. This research explores the
potential of our hybrid approach that relies on both, lexical and
machine learning techniques for detection of Ekman’s six
emotional categories in user’s text. The initial results of the
performance evaluation of the proposed hybrid approach are
encouraging and comparable to related research. A
demonstrative mobile application that employs the proposed
approach was developed to engage the users in a dialogue that
solicits their reflections on various daily events and provides
appropriate affective responses.
Subjects
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