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Found 3 papers, 3 papers with code
Synthesizing Sentiment-Controlled Feedback For Multimodal Text and Image Data
It implements an interpretability technique to analyze the contribution of textual and visual features during the generation of uncontrolled and controlled feedback.
Interpretable Multimodal Emotion Recognition using Hybrid Fusion of Speech and Image Data
A new interpretability technique has been developed to identify the important speech & image features leading to the prediction of particular emotion classes.
Hybrid Fusion Based Interpretable Multimodal Emotion Recognition with Limited Labelled Data
This paper proposes a multimodal emotion recognition system, VIsual Spoken Textual Additive Net (VISTA Net), to classify emotions reflected by multimodal input containing image, speech, and text into discrete classes.
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