Affective Computing
Language and vocabulary have emerged from emotions that were perceived. In this research we try to walk backwards to analyse emotions from language.
COGMEN: COntextualized GNN based Multimodal Emotion recognitioN
Abhinav Joshi, Ashwani Bhat, Ayush Jain, Atin Singh, Ashutosh Modi
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Shapes of Emotions: Multimodal Emotion Recognition in Conversations via Emotion Shifts
Keshav Bansal, Harsh Agarwal, Abhinav Joshi, Ashutosh Modi
Proceedings of the First Workshop on Performance and Interpretability Evaluations of Multimodal, Multipurpose, Massive-Scale Models
CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations
Divyaksh Shukla, Ritesh Baviskar, Dwijesh Gohil, Aniket Tiwari, Atul Shree, Ashutosh Modi
Findings of the Association for Computational Linguistics: ACL 2025
Exploration Lab IITK at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
Tafazzul Nadeem, Riyansha Singh, Suyamoon Pathak, Ashutosh Modi
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
IITK at SemEval-2024 Task 10: Who is the speaker? Improving Emotion Recognition and Flip Reasoning in Conversations via Speaker Embeddings
Shubham Patel, Divyaksh Shukla, Ashutosh Modi
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)