Conversation Understanding

Conversation understanding aims to enable computers to comprehend the nuances of human dialogue, encompassing aspects like emotion recognition, context awareness, and structural analysis. Current research heavily utilizes graph neural networks and transformer architectures to model the complex relationships between utterances within a conversation, incorporating multimodal data (text, audio, video) and addressing challenges like dialect variation and incomplete information. These advancements are crucial for improving applications such as chatbots, hate speech detection, and the development of more natural and effective human-computer interaction systems.