User and context adaptive neural networks for emotion recognition

Caridakis, G; Karpouzis, K; Kollias, S

dc.contributor.author	Caridakis, G	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:45:50Z
dc.date.available	2014-03-01T02:45:50Z
dc.date.issued	2008	en
dc.identifier.issn	0925-2312	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32421
dc.subject	Emotion recognition	en
dc.subject	Neural networks	en
dc.subject	User and context adaptation	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	Electric currents	en
dc.subject.other	Face recognition	en
dc.subject.other	Flow interactions	en
dc.subject.other	Human computer interaction	en
dc.subject.other	Knowledge management	en
dc.subject.other	Vegetation	en
dc.subject.other	Adaptation procedures	en
dc.subject.other	Adaptation requirements	en
dc.subject.other	Adaptive neural networks	en
dc.subject.other	Data sets	en
dc.subject.other	Emotion analysis	en
dc.subject.other	Emotion recognition	en
dc.subject.other	Emotion recognitions	en
dc.subject.other	Emotional states	en
dc.subject.other	Experimental studies	en
dc.subject.other	HUMAINE	en
dc.subject.other	Human-computer interactions	en
dc.subject.other	Multi modalities	en
dc.subject.other	Network of excellences	en
dc.subject.other	Neural network architectures	en
dc.subject.other	User and context adaptation	en
dc.subject.other	Neural networks	en
dc.subject.other	accuracy	en
dc.subject.other	adaptive behavior	en
dc.subject.other	artificial neural network	en
dc.subject.other	automated pattern recognition	en
dc.subject.other	computer interface	en
dc.subject.other	computer system	en
dc.subject.other	conceptual framework	en
dc.subject.other	conference paper	en
dc.subject.other	controlled study	en
dc.subject.other	emotional intelligence	en
dc.subject.other	experimental study	en
dc.subject.other	facial expression	en
dc.subject.other	female	en
dc.subject.other	human	en
dc.subject.other	human computer interaction	en
dc.subject.other	human experiment	en
dc.subject.other	learning environment	en
dc.subject.other	male	en
dc.subject.other	normal human	en
dc.subject.other	priority journal	en
dc.title	User and context adaptive neural networks for emotion recognition	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1016/j.neucom.2007.11.043	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.neucom.2007.11.043	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Recognition of emotional states of users in human-computer interaction (HCI) has been shown to be highly dependent on individual human characteristics and way of behavior. Multimodality is a key issue in achieving more accurate results; however, fusing different modalities is a difficult issue in emotion analysis. Emotion recognition systems are generally either rule-based or extensively trained through emotionally colored HCI data sets. in either case, such systems need to take into account, i.e., adapt their knowledge to, the specific user or context of interaction. Neural networks fit well with the adaptation requirement, by collecting and analyzing data from specific environments. An effective approach is presented in this paper, which uses neural network architectures to both detect the need for adaptation of their knowledge, and adapt it through an efficient adaptation procedure. An experimental study with emotion datasets generate in the framework of the EC IST Humaine Network of Excellence. (C) 2008 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Neurocomputing	en
dc.identifier.doi	10.1016/j.neucom.2007.11.043	en
dc.identifier.isi	ISI:000259121100016	en
dc.identifier.volume	71	en
dc.identifier.issue	13-15	en
dc.identifier.spage	2553	en
dc.identifier.epage	2562	en