ArticlePeerJ. Computer science2025
UMEDNet: a multimodal approach for emotion detection in the Urdu language.
Article in PeerJ. Computer science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Emotion detection is a critical component of interaction between human and computer systems, more especially affective computing, and health screening. Integrating video, speech, and text information provides better coverage of the basic and derived affective states with improved estimation of verbal and non-verbal behavior. However, there is a lack of systematic preferences and models for the detection of emotions in low-resource languages such as Urdu. To this effect, we propose Urdu Multimodal Emotion Detection Network (UMEDNet), a new emotion detection model for Urdu that works with video, speech, and text inputs for a better understanding of emotion. To support our proposed UMEDNet, we created the Urdu Multimodal Emotion Detection (UMED)
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