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Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2025CC BY V4.0, Open
Conference proceeding
The Art of Talking Machines: A Comprehensive Literature Review of Conversational User Interfaces
CUI '25: Proceedings of the 7th ACM Conference on Conversational User Interfaces, pp 1-18
07 Jul 2025
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Abstract
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.
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Details
- Title
- The Art of Talking Machines: A Comprehensive Literature Review of Conversational User Interfaces
- Creators
- Mohammad Namvarpour (Corresponding Author) - Drexel University, Information ScienceAfsaneh Razi - Drexel University, Information Science
- Publication Details
- CUI '25: Proceedings of the 7th ACM Conference on Conversational User Interfaces, pp 1-18
- Publisher
- Association for Computing Machinery
- Number of pages
- 18
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:001539402100043
- Scopus ID
- 2-s2.0-105011584985
- Other Identifier
- 991022063542304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics
- Computer Science, Interdisciplinary Applications
- Computer Science, Software Engineering