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        <title>Do Multimodal Emotion Recognition Models Tackle Ambiguity?</title>
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    <name type="personal">
        <namePart type="given">Hélène</namePart>
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        <namePart type="given">Engelbert</namePart>
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            <namePart type="given">Patrizia</namePart>
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    <abstract>Most databases used for emotion recognition assign a single emotion to data samples. This does not match with the complex nature of emotions: we can feel a wide range of emotions throughout our lives with varying degrees of intensity. We may even experience multiple emotions at once. Furthermore, each person physically expresses emotions differently, which makes emotion recognition even more challenging: we call this emotional ambiguity. This paper investigates the problem as a review of ambiguity in multimodal emotion recognition models. To lay the groundwork, the main representations of emotions along with solutions for incorporating ambiguity are described, followed by a brief overview of ambiguity representation in multimodal databases. Thereafter, only models trained on a database that incorporates ambiguity have been studied in this paper. We conclude that although databases provide annotations with ambiguity, most of these models do not fully exploit them, showing that there is still room for improvement in multimodal emotion recognition systems.</abstract>
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%0 Conference Proceedings
%T Do Multimodal Emotion Recognition Models Tackle Ambiguity?
%A Tran, Hélène
%A Falih, Issam
%A Goblet, Xavier
%A Mephu Nguifo, Engelbert
%Y Paggio, Patrizia
%Y Gatt, Albert
%Y Tanti, Marc
%S Proceedings of the 2nd Workshop on People in Vision, Language, and the Mind
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F tran-etal-2022-multimodal
%X Most databases used for emotion recognition assign a single emotion to data samples. This does not match with the complex nature of emotions: we can feel a wide range of emotions throughout our lives with varying degrees of intensity. We may even experience multiple emotions at once. Furthermore, each person physically expresses emotions differently, which makes emotion recognition even more challenging: we call this emotional ambiguity. This paper investigates the problem as a review of ambiguity in multimodal emotion recognition models. To lay the groundwork, the main representations of emotions along with solutions for incorporating ambiguity are described, followed by a brief overview of ambiguity representation in multimodal databases. Thereafter, only models trained on a database that incorporates ambiguity have been studied in this paper. We conclude that although databases provide annotations with ambiguity, most of these models do not fully exploit them, showing that there is still room for improvement in multimodal emotion recognition systems.
%U https://aclanthology.org/2022.pvlam-1.2
%P 6-11

Markdown (Informal)

[Do Multimodal Emotion Recognition Models Tackle Ambiguity?](https://aclanthology.org/2022.pvlam-1.2) (Tran et al., PVLAM 2022)

• Do Multimodal Emotion Recognition Models Tackle Ambiguity? (Tran et al., PVLAM 2022)

ACL

• Hélène Tran, Issam Falih, Xavier Goblet, and Engelbert Mephu Nguifo. 2022. Do Multimodal Emotion Recognition Models Tackle Ambiguity?. In Proceedings of the 2nd Workshop on People in Vision, Language, and the Mind, pages 6–11, Marseille, France. European Language Resources Association.