Turn Taking

Turn-taking, the fundamental process of alternating speech in conversation, is a key area of research in computational linguistics and human-computer interaction. Current research focuses on developing robust algorithms, often employing neural networks and large language models, to automatically segment conversations into turns, predict turn transitions and backchannels, and even evaluate the naturalness of turn-taking cues in synthetic speech. These advancements are crucial for improving the realism and effectiveness of conversational AI systems, as well as providing powerful new tools for analyzing human interaction in large conversational datasets.