The Art of Talking Machines: A Comprehensive Literature Review of Conversational User Interfaces

DOI

Conversational User Interfaces (CUIs) enable human-like interactions via voice, text, and multimodal communication, driven by natural language processing and machine learning. Prior literature reviews have primarily focused on specific application domains or design aspects, lacking an integrated, multi-dimensional analysis. This study addresses this gap by providing a structured framework synthesizing CUI research into interface design, system development, and ethical considerations. Our analysis highlights advancements in CUI design, such as dialogue structure, multimodal interactions, and adaptability. It also reveals persistent challenges, including bias in persona design, trust calibration, and data privacy. System development benefits from improvements in NLP, conversation memory, and multilingual capabilities. Ethical considerations, including social bias, user autonomy, and transparency, remain central to discussions on responsible CUI design. By analyzing existing research, we identify key gaps and suggest future directions, including multilingual and culturally adaptive CUIs, privacy-preserving AI techniques, and enhanced reasoning mechanisms for context-aware interactions.