A Survey of Conversational Styles and Systems

Conversational systems are an emerging area in natural language processing. This survey paper provides a comprehensive overview of architectures, methods, and datasets used to design the development of conversational agents. We have examined various conversational styles and system designs, ranging from rule-based to generative artificial intelligence-based systems. Our survey analyzes non-exhaustive lists of popular datasets for training conversational agents and identifies key methodologies employed in conversational agent construction. By synthesizing existing knowledge, this survey contributes to a better understanding of state-of-the-art conversational AI and highlights significant trends and challenges in the field. The insights drawn from this study can guide future research and development efforts to enhance conversational agents' capabilities and applications across diverse domains.