Act Classification

Dialogue act classification (DAC) aims to automatically identify the communicative intent behind utterances in conversations, a crucial step for building effective human-computer interaction systems. Current research focuses on improving DAC accuracy through advanced model architectures like transformers, incorporating contextual information (e.g., speaker, time, and task structure), and leveraging diverse features such as prosody and part-of-speech cues. These advancements are driving progress in various applications, including task-oriented dialogues, educational settings, and mental health counseling, where accurate understanding of conversational intent is paramount.