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http://hdl.handle.net/1893/16515| Appears in Collections: | Computing Science and Mathematics Book Chapters and Sections |
| Peer Review Status: | Refereed |
| Title: | Sentic Avatar: Multimodal Affective Conversational Agent with Common Sense |
| Author(s): | Cambria, Erik Hupont, Isabelle Hussain, Amir Cerezo, Eva Baldassarri, Sandra |
| Contact Email: | ahu@cs.stir.ac.uk |
| Editor(s): | Esposito, A Esposito, AM Martone, R Muller, VC Scarpetta, G |
| Citation: | Cambria E, Hupont I, Hussain A, Cerezo E & Baldassarri S (2011) Sentic Avatar: Multimodal Affective Conversational Agent with Common Sense. In: Esposito A, Esposito A, Martone R, Muller V & Scarpetta G (eds.) Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces. Theoretical and Practical Issues: Third COST 2102 International Training School, Caserta, Italy, March 15-19, 2010, Revised Selected Papers. Lecture Notes in Computer Science, 6456. Berlin Heidelberg: Springer, pp. 81-95. http://link.springer.com/chapter/10.1007%2F978-3-642-18184-9_8; https://doi.org/10.1007/978-3-642-18184-9_8 |
| Keywords: | AI Sentic Computing NLP Facial Expression Analysis Sentiment Analysis Multimodal Affective HCI Conversational Agents Internet Moral and ethical aspects. Social Environment Biometric Identification |
| Issue Date: | 2011 |
| Date Deposited: | 12-Jul-2011 |
| Series/Report no.: | Lecture Notes in Computer Science, 6456 |
| Abstract: | The capability of perceiving and expressing emotions through different modalities is a key issue for the enhancement of human-computer interaction. In this paper we present a novel architecture for the development of intelligent multimodal affective interfaces. It is based on the integration of Sentic Computing, a new opinion mining and sentiment analysis paradigm based on AI and Semantic Web techniques, with a facial emotional classifier and Maxine, a powerful multimodal animation engine for managing virtual agents and 3D scenarios. One of the main distinguishing features of the system is that it does not simply perform emotional classification in terms of a set of discrete emotional lables but it operates in a continuous 2D emotional space, enabling the integration of the different affective extraction modules in a simple and scalable way. |
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| URL: | http://link.springer.com/chapter/10.1007%2F978-3-642-18184-9_8 |
| DOI Link: | 10.1007/978-3-642-18184-9_8 |
| Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Sentic Avatar.pdf | Fulltext - Published Version | 5.1 MB | Adobe PDF | Under Embargo until 3000-12-01 Request a copy |
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