The IBM natural conversation framework: a new paradigm for conversational UX design
Abstract
User interfaces that take human conversation as their interaction metaphor work fundamentally differently than those that employ spatial metaphors, such as a desktop or a page. While the fundamenta...
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Anthropomorphic agents come with the promise of new kinds of user interfaces, spurring advances in the emerging field of conversational UX.
“Anthropomorphic agents come with the promise of new kinds of user interfaces, spurring advances in the emerging field of conversational UX (73, 74).”
From The benefits and dangers of anthropomorphic conversational agents (2025) · cites this paper as [73]
Cites
Advances in neural information processing systems 7
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90463-0 · Cited by 14,759 · see citing works
A simplest systematics for the organization of turn-taking for conversation
Sacks, H., Schegloff, E. A., & Jefferson, G. (1974) · Language · doi:10.2307/412243 · Cited by 11,350 · see citing works
Speech recognition with deep recurrent neural networks
Graves, A., Mohamed, A.-R., & Hinton, G. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6638947 · Cited by 8,893 · see citing works
Norman, D. A. (2016) · Vahlen eBooks · doi:10.15358/9783800648108 · Cited by 6,390 · see citing works
The Preference for Self-Correction in the Organization of Repair in Conversation
Schegloff, E. A., Jefferson, G., & Sacks, H. (1977) · Language · doi:10.2307/413107 · Cited by 5,150 · see citing works
Sequence Organization in Interaction
Schegloff, E. A. (2007) · Cambridge University Press eBooks · doi:10.1017/cbo9780511791208 · Cited by 4,955 · see citing works
SCHEGLOFF, E. A., & SACKS, H. (1973) · Semiotica · doi:10.1515/semi.1973.8.4.289 · Cited by 4,589 · see citing works
A Pattern Language: Towns, Buildings, Construction
Alexander, C., Ishikawa, S., Silverstein, M., Jacobson, M., Fiksdahl-King, I., & Angel, S. (1977) · Cited by 4,555 · see citing works
Everyday Language: Studies in Ethnomethodology
Psathas, G. (1979) · Human Studies · Cited by 2,342 · see citing works
Repair After Next Turn: The Last Structurally Provided Defense of Intersubjectivity in Conversation
Schegloff, E. A. (1992) · American Journal of Sociology · doi:10.1086/229903 · Cited by 1,820 · see citing works
Confirming Allusions: Toward an Empirical Account of Action
Schegloff, E. A. (1996) · American Journal of Sociology · doi:10.1086/230911 · Cited by 1,163 · see citing works
Chowdhury, G. G. (2003) · Annual Review of Information Science and Technology · doi:10.1002/aris.1440370103 · Cited by 863 · see citing works
Neural Network Methods for Natural Language Processing
Goldberg, Y. (2017) · Synthesis Lectures on Human Language Technologies · doi:10.1007/978-3-031-02165-7 · Cited by 821 · see citing works
Voice Interfaces in Everyday Life
Porcheron, M., Fischer, J. E., Reeves, S., & Sharples, S. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174214 · Cited by 717 · cited 3× · see citing works
“On the one hand, its methods of qualitative, sequential analysis of transcripts can adapted to recordings of humans’ interaction with automated agents (Porcheron et al., 2018) and design insights can be drawn from the findings.”
BackgroundMethodBuilding applied natural language generation systems
Reiter, E., & Dale, R. (1997) · Natural Language Engineering · doi:10.1017/s1351324997001502 · Cited by 653 · see citing works
McTear, M., Callejas, Z., & Griol, D. (2016) · doi:10.1007/978-3-319-32967-3 · Cited by 594 · see citing works
Chaves, A. P., & Gerosa, M. A. (2021) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1841438 · Cited by 572 · see citing works
Entity-Relation Extraction as Multi-Turn Question Answering
Li, X., Yin, F., Sun, Z., Li, X., Yuan, A., Chai, D., Zhou, M., & Li, J. (2019) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p19-1129 · Cited by 406 · see citing works
Designing SpeechActs: issues in speech user interfaces
Yankelovich, N., Levow, G.-A., & Marx, M. (1995) · Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '95 · doi:10.1145/223904.223952 · Cited by 250 · see citing works
Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns
Ashktorab, Z., Jain, M., Liao, Q. V., & Weisz, J. D. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300484 · Cited by 224 · see citing works
Detecting Phishing Attacks Using Natural Language Processing and Machine Learning
Peng, T., Harris, I. G., & Sawa, Y. (2018) · IEEE International Conference on Semantic Computing (ICSC) · doi:10.1109/icsc.2018.00056 · Cited by 171 · see citing works
Proceedings of the Sixth International Joint Conference on Natural Language Processing
Mitkov, R., & Park, J. C. (2013) · International Joint Conference on Natural Language Processing · Cited by 144 · see citing works
Conversational UX Design: A Practitioner's Guide to the Natural Conversation Framework
Research-Almaden, I., Moore, R. J., Arar, R., & Research-Almaden, I. (2019) · doi:10.1145/3304087 · Cited by 118 · cited 18× · see citing works
“However, the spatial interaction metaphors of these areas of visual design largely do not apply to the design of conversational user interfaces (Moore & Arar, 2019; Moore et al., 2020; Murad et al., 2021; Yankelovich et al., 1995).”
BackgroundMethodInfluentialSelf-citationFast, E., Chen, B., Mendelsohn, J., Bassen, J., & Bernstein, M. S. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174047 · Cited by 110 · see citing works
Avula, S., Chadwick, G., Arguello, J., & Capra, R. (2018) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3176349.3176380 · Cited by 80 · see citing works
Convey: Exploring the Use of a Context View for Chatbots
Jain, M., Kota, R., Kumar, P., & Patel, S. N. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174042 · Cited by 74 · see citing works
Hussain, S., & Ginige, A. (2018) · International Conference on Advanced Information Networking and Applications Workshops (WAINA) · doi:10.1109/waina.2018.00170 · Cited by 57 · see citing works
How Turn-Taking Strategies Influence Users’ Impressions of an Agent
ter Maat, M., Truong, K. P., & Heylen, D. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15892-6_48 · Cited by 56 · see citing works
Applying the Technology of Conversation to the Technology for Conversation
Frohlich, D. M., & Luff, P. (1990) · Elsevier eBooks · doi:10.1016/b978-0-08-050264-9.50014-2 · Cited by 51 · see citing works
Studies in Conversational UX Design
(2018) · Human-computer interaction series · doi:10.1007/978-3-319-95579-7 · Cited by 51 · see citing works
Finding a New Voice: Transitioning Designers from GUI to VUI Design
Murad, C., Munteanu, C., Cowan, B. R., & Clark, L. (2021) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3469595.3469617 · Cited by 30 · see citing works
Scaling UX with design systems
Churchill, E. F. (2019) · interactions · doi:10.1145/3352681 · Cited by 22 · see citing works
Enhancement of Conversational Agents By Means of Multimodal Interaction
López-Cózar, R., Callejas, Z., Espejo, G., & Griol, D. (2011) · Conversational Agents and Natural Language Interaction · doi:10.4018/978-1-60960-617-6.ch010 · Cited by 18 · see citing works
Repair Work in Human-Computer Interaction
Raudaskoski, P. L. (1990) · Elsevier eBooks · doi:10.1016/b978-0-08-050264-9.50012-9 · Cited by 18 · see citing works
Design Systems for Conversational UX
Moore, R. J., Liu, E. Y., Mishra, S., & Ren, G. (2020) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3405755.3406150 · Cited by 18 · see citing works
Self-citationNADIA: A Simplified Approach Towards the Development of Natural Dialogue Systems
Berg, M. M. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-19581-0_12 · Cited by 16 · see citing works
Story Analysis Using Natural Language Processing and Interactive Dashboards
Mitri, M. (2020) · Journal of Computer Information Systems · doi:10.1080/08874417.2020.1774442 · Cited by 10 · see citing works
A Comparative Study to Understanding about Poetics Based on Natural Language Processing
Zhang, L., & Gao, J. (2017) · Open Journal of Modern Linguistics · doi:10.4236/ojml.2017.75017 · Cited by 7 · see citing works
Effects of Naturalistic Variation in Goal-Oriented Dialog
Ganhotra, J., Moore, R. J., Joshi, S., & Wadhawan, K. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.358 · Cited by 7 · see citing works
Self-citationTowards Personalization of Spoken Dialogue System Communication Strategies
Gordon, C., Georgila, K., Yanov, V., & Traum, D. R. (2020) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-8395-7_11 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The benefits and dangers of anthropomorphic conversational agents
Peter, S., Riemer, K., & West, J. D. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2415898122 · Cited by 110 · see citing works
Interactive repair and the foundations of language
Dingemanse, M., & Enfield, N. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.09.003 · Cited by 65 · see citing works
Heidari, A., Navimipour, N. J., Zeadally, S., & Chamola, V. (2024) · Internet Technology Letters · doi:10.1002/itl2.530 · Cited by 56 · see citing works
Cooking With Agents: Designing Context-aware Voice Interaction
Jaber, R. N., Zhong, S., Kuoppamäki, S., Hosseini, A., Gessinger, I., Brumby, D., Cowan, B. R., & Mcmillan, D. (2024) · International Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642183 · Cited by 48 · see citing works
Faruk, L. I. D., Pal, D., Funilkul, S., Perumal, T., & Mongkolnam, P. (2024) · International journal of human computer interactions · doi:10.1080/10447318.2024.2359206 · Cited by 24 · see citing works
AI in situated action: a scoping review of ethnomethodological and conversation analytic studies
Mlynář, J., de Rijk, L., Liesenfeld, A., Stommel, W., & Albert, S. (2025) · AI & SOCIETY · doi:10.1007/s00146-024-01919-x · Cited by 18 · see citing works
Følstad, A., Law, E. L.-C., & van As, N. (2024) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3690383 · Cited by 17 · see citing works
AI Transforming Business and Everyday Life
Bialkova, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-56471-0_9 · Cited by 12 · see citing works
Brandt, A., Hazel, S., McKinnon, R., Sideridou, K., Tindale, J., & Ventoura, N. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3603758 · Cited by 9 · see citing works
Chatbot User Experience: Design and Evaluation
Peras, D. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-76806-4_6 · Cited by 4 · see citing works
Moore, R. J., An, S., & Marrese, O. H. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3641026 · Cited by 4 · see citing works
Self-citationEnhancing the Natural Conversation Experience Through Conversation Analysis – A Design Method
Hazel, S., & Brandt, A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48038-6_6 · Cited by 4 · see citing works
You Can Do It! or Can We? Personal Pronouns and Their Impact on Consumer Goal Pursuit
Sadowski, S., & Das, E. (2025) · Psychology and Marketing · doi:10.1002/mar.70005 · Cited by 3 · see citing works
Conversation Design: The Evolving Paradigm in Technical and Professional Communication
Shalamova, N., & Verhulsdonck, G. (2025) · Communication Design Quarterly · doi:10.1145/3787586.3787589 · Cited by 2 · see citing works
Lee, Y., Sargsyan, L., Choi, S., & Kim, S.-H. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2530058 · Cited by 2 · see citing works
DECI: A Tutorial on Designing Effective Conversational Interfaces
Gadiraju, U., Abbas, T., & Allen, G. (2023) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3581754.3584165 · Cited by 1 · see citing works
Psychophysiological Research in the Design of Useful Interfaces for e-Learning Materials
Piwowarski, M., Nermend, M., & Nermend, K. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-66761-9_18 · Cited by 1 · see citing works
Moore, R. J., An, S., Gala, J. P., & Jadav, D. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714401 · Cited by 1 · see citing works
Self-citationHanafi, M. F., Reiss, F. R., Katsis, Y., Moore, R. J., Falakmasir, M. H., Wang, P. C., Wood, D., & Liu, C. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713312 · Cited by 1 · see citing works
Self-citationFrom clicks to conversations: the rise of conversational UI powered by ai
Goli, V. R. (2025) · Global Journal of Engineering and Technology Advances · doi:10.30574/gjeta.2025.23.3.0172 · Cited by 1 · see citing works
Machine-Assisted Error Discovery in Conversational AI Systems
Hanafi, M. F., Reiss, F. R., Katsis, Y., Moore, R. J., Wood, D., Falakmasir, M. H., & Liu, C. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3651120 · Cited by 1 · see citing works
Self-citationCase Studies: Redefining Web Design and Co-creation
Hutson, J., Lively, J., Robertson, B., Cotroneo, P., & Lang, M. (2023) · Springer series on cultural computing · doi:10.1007/978-3-031-45127-0_7
Bharathi, S. V., & Bhosale, S. (2024) · Springer eBooks · doi:10.1007/978-981-99-6984-5_26
Navigating Ethical Challenges of AI Chatbots for Sex Therapy
Fu, M., & Chan, W. (2025) · Oxford University Press eBooks · doi:10.1093/9780198945215.003.0075 · Cited by 1 · see citing works
The AI Reading Conundrum and Its Implications for Pedagogy
Eaton, C. (2024) · Double Helix A Journal of Critical Thinking and Writing · doi:10.37514/dbh-j.2024.12.1.03
WEB PROGRAMMING AND MOBILE DEVELOPMENT: UX/UI SOLUTIONS FOR PROTECTING USERS' PERSONAL DATA
Читулян, В., Oleinikov, I., Ananchenko, O., & Dziuba, V. (2025) · Cybersecurity Education Science Technique · doi:10.28925/2663-4023.2025.30.992
- Authors
- Moore, R. J., An, S., & Ren, G.-J.
- Affiliations
- IBM Research - Almaden (US)
- Georgia Institute of Technology (US)
- Corresponding author
- Moore, Robert J.
- Venue
- Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2022-06-13
- Volume
- 38
- Issue
- 3-4
- Pages
- 168-193
- ISSN
- 0737-0024 (ISSN-L)
- 1532-7051
- OpenAlex
- W4282559157
- Cited by
- 26
- References
- 40
- Citations by year
- 2025: 9 · 2024: 12 · 2023: 5
- FWCI
- 2.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human-Computer Interaction (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- natural conversation, conversational interfaces, interaction metaphors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review