IEMOCAP

IEMOCAP is a dataset that contains multimodal conversational data used to evaluate utterance-level emotion recognition by integrating textual, acoustic, and visual cues.

Papers using IEMOCAP (7)

Disentangled Dual-Branch Graph Learning for Conversational Emotion Recognition2026COGMEN: COntextualized GNN based Multimodal Emotion recognitioN2022 · 8 citesA Contextualized Real-Time Multimodal Emotion Recognition for Conversational Agents using Graph Convolutional Networks in Reinforcement Learning2023 · 1 citesEffective Context Modeling Framework for Emotion Recognition in Conversations2024 · 1 citesLineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks2023Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation2025A Graph Isomorphism Network with Weighted Multiple Aggregators for Speech Emotion Recognition2022