Conversational Dataset

Conversational datasets are collections of human-human or human-machine dialogues used to train and evaluate conversational AI models. Current research focuses on creating more realistic and diverse datasets that capture the nuances of real-world conversations, including disfluencies, diverse accents, and domain-specific terminology, often leveraging large language models for data augmentation and generation. These efforts aim to improve the performance and robustness of conversational AI systems across various tasks, such as question answering, entity linking, and emotion recognition, ultimately leading to more natural and engaging human-computer interactions. The development of high-quality, diverse conversational datasets is crucial for advancing the field and enabling the creation of more effective and beneficial conversational AI applications.