Multimodal Emotion Recognition in Polish (Student Consortium)

Rupauliha, Kritika; Goyal, Aman; Saini, Aman; Shukla, Abhinav; Swaminathan, Sridhar

doi:10.1109/bigmm50055.2020.00054

Cited by 2 publications

(1 citation statement)

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“…Emotion recognition is a challenging task due to the difficulty of discrimination [ 24 ] and diverse expression modalities [ 25 ]. To solve the challenge of abstraction of emotion, researchers tried to use different features to discriminate different emotions.…”

Section: Related Workmentioning

confidence: 99%

Incorporating Interpersonal Synchronization Features for Automatic Emotion Recognition from Visual and Audio Data during Communication

Quan

Miyake

Nozawa

2021

Sensors

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During social interaction, humans recognize others’ emotions via individual features and interpersonal features. However, most previous automatic emotion recognition techniques only used individual features—they have not tested the importance of interpersonal features. In the present study, we asked whether interpersonal features, especially time-lagged synchronization features, are beneficial to the performance of automatic emotion recognition techniques. We explored this question in the main experiment (speaker-dependent emotion recognition) and supplementary experiment (speaker-independent emotion recognition) by building an individual framework and interpersonal framework in visual, audio, and cross-modality, respectively. Our main experiment results showed that the interpersonal framework outperformed the individual framework in every modality. Our supplementary experiment showed—even for unknown communication pairs—that the interpersonal framework led to a better performance. Therefore, we concluded that interpersonal features are useful to boost the performance of automatic emotion recognition tasks. We hope to raise attention to interpersonal features in this study.

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Section: Related Workmentioning

confidence: 99%