Dialogue Datasets

Dialogue datasets are crucial for training and evaluating conversational AI systems, aiming to create more natural and effective human-computer interactions. Current research focuses on improving the quality and diversity of these datasets, addressing limitations such as a lack of spoken language data, insufficient representation of complex linguistic phenomena (like indirect requests), and biases towards certain languages or dialects. Large language models (LLMs) are widely used for data augmentation, annotation, and model development, with ongoing efforts to enhance their robustness and efficiency for various dialogue tasks, including task-oriented dialogues and open-domain conversations. These advancements are vital for building more sophisticated and inclusive conversational AI systems across diverse applications.