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dc.contributor.authorSánchez-Rada, J. Fernando
dc.contributor.authorIglesias, Carlos A.
dc.contributor.authorSagha, Hesam
dc.contributor.authorSchuller, Björn
dc.contributor.authorIan D. Wood, Ian D.
dc.contributor.authorBuitelaar, Paul
dc.date.accessioned2018-09-05T11:33:10Z
dc.date.available2018-09-05T11:33:10Z
dc.date.issued2017-10-23
dc.identifier.citationSánchez-Rada, J. Fernando, Iglesias, Carlos A., Sagha, Hesam, Schuller, Björn, Ian D. Wood, Ian D., & Buitelaar, Paul. (2017). Multimodal multimodel emotion analysis as linked data. Paper presented at the 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), San Antonio, TX, USA, 23-26 October, pp. 111-116, doi: 10.1109/ACIIW.2017.8272599en_IE
dc.identifier.isbn10.1109/ACIIW.2017.8272599
dc.identifier.urihttp://hdl.handle.net/10379/10030
dc.description.abstractThe lack of a standard emotion representation model hinders emotion analysis due to the incompatibility of annotation formats and models from different sources, tools and annotation services. This is also a limiting factor for multimodal analysis, since recognition services from different modalities (audio, video, text) tend to have different representation models (e. g., continuous vs. discrete emotions). This work presents a multi-disciplinary effort to alleviate this problem by formalizing conversion between emotion models. The specific contributions are: i) a semantic representation of emotion conversion; ii) an API proposal for services that perform automatic conversion; iii) a reference implementation of such a service; and iv) validation of the proposal through use cases that integrate different emotion models and service providers.en_IE
dc.description.sponsorshipThe research leading to these results has received funding from the European Union‘s Horizon 2020 Programme research and innovation programme under grant agreement No. 644632 (MixedEmotions)en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherIEEEen_IE
dc.relation.ispartof3rd International Workshop on Emotion and Sentiment in Social and Expressive Media: User Engagement and Interactionen
dc.subjectEmotional analysisen_IE
dc.subjectLinked dataen_IE
dc.titleMultimodal multimodel emotion analysis as linked dataen_IE
dc.typeConference Paperen_IE
dc.date.updated2018-06-29T09:54:42Z
dc.local.publishedsourcehttps://dx.doi.org/10.1109/ACIIW.2017.8272599en_IE
dc.description.peer-reviewednon-peer-reviewed
dc.contributor.funderHorizon 2020en_IE
dc.internal.rssid14558716
dc.local.contactIan Wood. Email: ian.wood@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::IA/644632/EU/Social Semantic Emotion Analysis for Innovative Multilingual Big Data Analytics Markets/MixedEmotionsen_IE
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