Multi Party Dialogue

Multi-party dialogue research focuses on understanding and modeling conversations involving more than two participants, aiming to improve the capabilities of conversational AI agents in complex social interactions. Current research emphasizes developing models that effectively handle long-term contextual dependencies, speaker identification, and the nuanced emotional dynamics within these dialogues, often employing deep neural networks, graph convolutional networks, and reinforcement learning techniques. This field is crucial for advancing human-computer interaction, particularly in applications like collaborative virtual assistants, interactive entertainment, and the analysis of real-world social interactions.