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        <namePart type="given">Jean-Benoit</namePart>
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        <name type="personal">
            <namePart type="given">Soujanya</namePart>
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    <abstract>Understanding expressed sentiment and emotions are two crucial factors in human multimodal language. This paper describes a Transformer-based joint-encoding (TBJE) for the task of Emotion Recognition and Sentiment Analysis. In addition to use the Transformer architecture, our approach relies on a modular co-attention and a glimpse layer to jointly encode one or more modalities. The proposed solution has also been submitted to the ACL20: Second Grand-Challenge on Multimodal Language to be evaluated on the CMU-MOSEI dataset. The code to replicate the presented experiments is open-source .</abstract>
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%0 Conference Proceedings
%T A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis
%A Delbrouck, Jean-Benoit
%A Tits, Noé
%A Brousmiche, Mathilde
%A Dupont, Stéphane
%Y Zadeh, Amir
%Y Morency, Louis-Philippe
%Y Liang, Paul Pu
%Y Poria, Soujanya
%S Second Grand-Challenge and Workshop on Multimodal Language (Challenge-HML)
%D 2020
%8 July
%I Association for Computational Linguistics
%C Seattle, USA
%F delbrouck-etal-2020-transformer
%X Understanding expressed sentiment and emotions are two crucial factors in human multimodal language. This paper describes a Transformer-based joint-encoding (TBJE) for the task of Emotion Recognition and Sentiment Analysis. In addition to use the Transformer architecture, our approach relies on a modular co-attention and a glimpse layer to jointly encode one or more modalities. The proposed solution has also been submitted to the ACL20: Second Grand-Challenge on Multimodal Language to be evaluated on the CMU-MOSEI dataset. The code to replicate the presented experiments is open-source .
%R 10.18653/v1/2020.challengehml-1.1
%U https://aclanthology.org/2020.challengehml-1.1
%U https://doi.org/10.18653/v1/2020.challengehml-1.1
%P 1-7

Markdown (Informal)

[A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis](https://aclanthology.org/2020.challengehml-1.1) (Delbrouck et al., Challenge-HML 2020)

• A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis (Delbrouck et al., Challenge-HML 2020)

ACL

• Jean-Benoit Delbrouck, Noé Tits, Mathilde Brousmiche, and Stéphane Dupont. 2020. A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis. In Second Grand-Challenge and Workshop on Multimodal Language (Challenge-HML), pages 1–7, Seattle, USA. Association for Computational Linguistics.