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dc.contributor.authorPaul Smith and Sam Redfern
dc.contributor.authorSmith, Paul
dc.contributor.authorRedfern, Sam
dc.identifier.citationPaul Smith and Sam Redfern (2010) Emotion Tracking for Remote Conferencing Applications using Neural Networks AICSen_US
dc.descriptionConference paperen_US
dc.description.abstractIn face-to-face work, discussion and negotiation relies strongly on non-verbal feedback, which provides important clues to negotiation states such as agreement/disagreement and understanding/confusion, as well as indicating the emotional states and reactions of those around us. With the continued rise of virtual teams, collaborative work increasingly requires tools to manage the reality of distributed and remote work, which is often hampered by a lack of social cohesion and such phenomena as participants multi-tasking rather than paying full attention. This paper discu sses the use of a neural network-based emotion recognition system and describes its application to the monitoring of presence and emotional states of participants in virtual meetings. Experimental analysis shows our Emotion Tracking Agent (ETA) to have marginally better accuracy at recognising universal emotions than human subjects presented with the same data.en_US
dc.publisherThe 21st National Conference on Artificial Intelligence and Cognitive Scienceen_US
dc.subjectNeural networksen_US
dc.subjectEmotion trackingen_US
dc.subjectVirtual teamsen_US
dc.titleEmotion Tracking for Remote Conferencing Applications using Neural Networks.en_US
dc.typeConference Paperen_US
dc.local.contactSam Redfern, Dept. Of Information Technology, I.T. Building, Nui Galway. 3670 Email:

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