At Your Service: Designing Voice Assistant Personalities to Improve Automotive User Interfaces
Open accessAbstract
This paper investigates personalized voice characters for in-car speech interfaces. In particular, we report on how we designed different personalities for voice assistants and compared them in a real world driving study. Voice assistants have become important for a wide range of use cases, yet current interfaces are using the same style of auditory response in every situation, despite varying user needs and personalities. To close this gap, we designed four assistant personalities (Friend, Admirer, Aunt, and Butler) and compared them to a baseline (Default) in a between-subject study in real traffic conditions. Our results show higher likability and trust for assistants that correctly match the user's personality while we observed lower likability, trust, satisfaction, and usefulness for incorrectly matched personalities, each in comparison with the Default character. We discuss design aspects for voice assistants in different automotive use cases.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Customizing a voice assistant's personality to the user can lead to higher trust.
“In addition, customizing a voice assistant's personality to the user can lead to higher trust [7], while gender does not impact users' trust in a voice assistant [59].”
From A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures (2023) · cites this paper as [7]
Users found VUI metaphors similar to themselves (in OCEAN traits) to be more likable and trustworthy.
“They found that users found metaphors that were similar to them (in terms of: openness, conscientiousness, extraversion, agreeableness, and neuroticism (OCEAN) [51]) were perceived to be more likable and trustworthy.”
From Examining Humanness as a Metaphor to Design Voice User Interfaces (2024) · cites this paper as [9]
About 31% of users would accept recommendations from conversational AI, like ChatGPT, without verifying them.
“A recent survey found that about 31% of users would accept recommendations from conver-sational AI, like ChatGPT, without verifying them.9”
From Examining Humanness as a Metaphor to Design Voice User Interfaces (2024) · cites this paper as [9]
Chatbot personality has been shown to affect trust.
“Chatbot personality has been shown to affect trust [11,12], engagement [6], subjective satisfaction [13,14], and consumer behavior [6].”
From Interacting with a Chatbot-Based Advising System: Understanding the Effect of Chatbot Personality and User Gender on Behavior (2022) · cites this paper as [11]
Users trust chatbot personalities similar to theirs in voice-based e-commerce and driving assistant chatbot applications.
“Related works show that users trust chatbot personalities similar to theirs [11,58] in the context of voice-based e-commerce and driving assistant chatbot-based applications.”
From Interacting with a Chatbot-Based Advising System: Understanding the Effect of Chatbot Personality and User Gender on Behavior (2022) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Quinlan, J. R. (1986) · Machine Learning · doi:10.1007/bf00116251 · Cited by 21,439 · see citing works
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003 · see citing works
Intelligent agents: theory and practice
Wooldridge, M., & Jennings, N. R. (1995) · The Knowledge Engineering Review · doi:10.1017/s0269888900008122 · Cited by 6,810 · see citing works
The Uncanny Valley [From the Field]
Mori, M., MacDorman, K., & Kageki, N. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2192811 · Cited by 3,542 · see citing works
Nass, C., Steuer, J., & Tauber, E. R. (1994) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/191666.191703 · Cited by 2,148 · see citing works
Construction and Evaluation of a User Experience Questionnaire
Laugwitz, B., Held, T., & Schrepp, M. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-89350-9_6 · Cited by 2,114 · see citing works
Emotional responses to music: The need to consider underlying mechanisms
Juslin, P. N., & Västfjäll, D. (2008) · Behavioral and Brain Sciences · doi:10.1017/s0140525x08005293 · Cited by 1,914 · see citing works
Establishing and maintaining long-term human-computer relationships
Bickmore, T. W., & Picard, R. W. (2005) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1067860.1067867 · Cited by 1,333 · cited 1× · see citing works
“In related work, Bickmore & Picard show a relational agent capable of social and emotional interaction, which was evaluated with high ratings for trust and likability [4].”
BackgroundLuger, E., & Sellen, A. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858288 · Cited by 1,176 · see citing works
Personality, coping, and coping effectiveness in an adult sample
McCrae, R. R., & Costa, P. T. (1986) · Journal of Personality · doi:10.1111/j.1467-6494.1986.tb00401.x · Cited by 1,118 · see citing works
A simple procedure for the assessment of acceptance of advanced transport telematics
Van Der Laan, J. D., Heino, A., & De Waard, D. (1997) · Transportation Research Part C: Emerging Technologies · doi:10.1016/s0968-090x(96)00025-3 · Cited by 873 · 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
“Conversational interfaces, or voice assistants, that is interfaces which are operated by voice input and respond with synthesized speech [41], have become ubiquitous through smart phones and home automation [41].”
BackgroundInfluentialWizard of Oz studies — why and how
Dahlbäck, N., Jönsson, A., & Ahrenberg, L. (1993) · Knowledge-Based Systems · doi:10.1016/0950-7051(93)90017-n · Cited by 706 · see citing works
Attention, distraction, and cognitive control under load
Lavie, N. (2010) · Current Directions in Psychological Science · doi:10.1177/0963721410370295 · Cited by 673 · see citing works
Pradhan, A., Mehta, K., & Findlater, L. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174033 · Cited by 448 · see citing works
Hergeth, S., Lorenz, L., Vilimek, R., & Krems, J. F. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815625744 · Cited by 355 · see citing works
Bickmore, T. W., Trinh, H., Olafsson, S., O'Leary, T. K., Asadi, R., Rickles, N. M., & Cruz, R. (2018) · Journal of Medical Internet Research · doi:10.2196/11510 · Cited by 308 · see citing works
McDuff, D., Mahmoud, A., Mavadati, M., Amr, M., Turcot, J., & el Kaliouby, R. (2016) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2851581.2890247 · Cited by 283 · see citing works
Can computer personalities be human personalities?
Nass, C., Moon, Y., Fogg, B. J., Reeves, B., & Dryer, C. (1995) · Conference companion on Human factors in computing systems - CHI '95 · doi:10.1145/223355.223538 · Cited by 251 · see citing works
Improving automotive safety by pairing driver emotion and car voice emotion
Nass, C., Jonsson, I.-M., Harris, H., Reaves, B., Endo, J., Brave, S., & Takayama, L. (2005) · CHI '05 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/1056808.1057070 · Cited by 249 · see citing works
A method to assess the driver mental workload: The driving activity load index (DALI)
Pauzié, A. (2008) · IET Intelligent Transport Systems · doi:10.1049/iet-its:20080023 · Cited by 248 · see citing works
A user-centered design approach to personalization
Kramer, J., Noronha, S., & Vergo, J. G. (2000) · Communications of the ACM · doi:10.1145/345124.345139 · Cited by 235 · see citing works
Integrating Models of Personality and Emotions into Lifelike Characters
André, E., Klesen, M., Gebhard, P., Allen, S., & Rist, T. (2000) · Lecture notes in computer science · doi:10.1007/10720296_11 · Cited by 192 · see citing works
HARK No More: On the Preregistration of CHI Experiments
Cockburn, A., Gutwin, C., & Dix, A. (2018) · International Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173715 · Cited by 159 · see citing works
Affective Grounding in Human-Robot Interaction
Jung, M. F. (2017) · Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction · doi:10.1145/2909824.3020224 · Cited by 142 · see citing works
First Impressions in Human--Agent Virtual Encounters
Cafaro, A., Vilhjálmsson, H. H., & Bickmore, T. (2016) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2940325 · Cited by 120 · see citing works
Multimodal interaction in the car
Pfleging, B., Schneegaß, S., & Schmidt, A. (2012) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/2390256.2390282 · Cited by 118 · see citing works
Self-citationThe Time Course of Emotional Responses to Music
Bigand, E., Filipic, S., & Lalitte, P. (2005) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1360.036 · Cited by 113 · see citing works
Comparison of manual vs. speech-based interaction with in-vehicle information systems
Maciej, J., & Vollrath, M. (2009) · Accident Analysis & Prevention · doi:10.1016/j.aap.2009.05.007 · Cited by 107 · see citing works
Die deutsche Version des Big Five Inventory 2 (BFI-2)
Danner, D., Rammstedt, B., Bluemke, M., Treiber, L., Berres, S., Soto, C., & John, O. (2016) · MADOC (University of Mannheim) · doi:10.6102/zis247 · Cited by 96 · see citing works
meCUE – Ein modularer Fragebogen zur Erfassung des Nutzungserlebens
Minge, M., & Riedel, L. (2013) · Oldenbourg Wissenschaftsverlag eBooks · doi:10.1524/9783486781229.89 · Cited by 72 · see citing works
Forming first impressions: The role of gender and normative accuracy in personality perception
Chan, M., Rogers, K. H., Parisotto, K. L., & Biesanz, J. C. (2010) · Journal of Research in Personality · doi:10.1016/j.jrp.2010.11.001 · Cited by 69 · see citing works
Demands on driver resources associated with introducing advanced technology into the vehicle
Wierwille, W. W. (1993) · Transportation Research Part C Emerging Technologies · doi:10.1016/0968-090x(93)90010-d · Cited by 61 · see citing works
The Effects of Situational Demands on Gaze, Speech and Gesture Input in the Vehicle
Roider, F., Rümelin, S., Pfleging, B., & Gross, T. (2017) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3122986.3122999 · Cited by 49 · see citing works
Self-citationAssessing Cognitive Demand during Natural Language Interactions with a Digital Driving Assistant
Large, D. R., Burnett, G., Anyasodo, B., & Skrypchuk, L. (2016) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3003715.3005408 · Cited by 43 · see citing works
Driver in the Loop: Best Practices in Automotive Sensing and Feedback Mechanisms
Riener, A., Jeon, M., Álvarez, I., & Frison, A.-K. (2017) · Human-computer interaction series · doi:10.1007/978-3-319-49448-7_11 · Cited by 43 · see citing works
Keeping up impressions: Inferential rules for impression change across the Big Five
Kammrath, L. K., Ames, D. R., & Scholer, A. A. (2007) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2006.04.006 · Cited by 31 · see citing works
A Survey on Different Means of Personalized Dialog Output for an Adaptive Personal Assistant
Schmidt, M., & Braunger, P. (2018) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3213586.3226198 · Cited by 28 · see citing works
Speech and driving - solution or problem?
Vollrath, M. (2007) · IET Intelligent Transport Systems · doi:10.1049/iet-its:20060052 · Cited by 23 · see citing works
Designing Robot Personality Based on Fictional Sidekick Characters
Luria, M. (2018) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3173386.3176912 · Cited by 21 · see citing works
Benefits of Personalization in the Context of a Speech-Based Left-Turn Assistant
Orth, D., Schömig, N., Mark, C., Jagiellowicz‐Kaufmann, M., Kolossa, D., & Heckmann, M. (2017) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3122986.3123004 · Cited by 17 · see citing works
What Kind of Mind Do I Want in My Robot?
Malle, B. F., & Magar, S. T. (2017) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3029798.3038378 · Cited by 14 · see citing works
Dialogue behaviour under high cognitive load
Villing, J. (2009) · doi:10.3115/1708376.1708423 · Cited by 12 · see citing works
Jarosch, O., & Bengler, K. J. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-96074-6_54 · Cited by 12 · see citing works
Personalization for Google Now
Thakur, S. (2016) · ACM Conference on Recommender Systems (RecSys) · doi:10.1145/2959100.2959192 · Cited by 9 · see citing works
Augmenting Visualization with Natural Language Translation of Interaction: A Usability Study
Nafari, M., & Weaver, C. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12126 · Cited by 8 · see citing works
Braun, M., Völkel, S. T., Hußmann, H., Frison, A.-K., Alt, F., & Riener, A. (2018) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3239092.3265963 · Cited by 7 · see citing works
Self-citationHeterogeneity in Customization of Recommender Systems By Users with Homogenous Preferences
Solomon, J. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858513 · Cited by 5 · see citing works
Flagged first, then by citations
Research works printed but not linked: 5
- Ignacio Alvarez, Hanan Alnizami, Jerone Dunbar, Andrea Johnson, France Jackson, and Juan E. Gilber. 2011. Designing Driver-Centric Natural Voice User Interfaces. In Adjunct Proceedings of the 3rd In- ternational Conference on Automotive User Interfaces and Interactive Vehicular Applications. online, 156-159.
- Michael Argyle. 1988. Bodily communication (second ed.). Routledge, New York, NY.
- Ewa Luger and Abigail Sellen. 2016. "Like Having a Really Bad PA": The Gulf Between User Expectation and Experience of Conversational Agents. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16). ACM, New York, NY, USA, 5286-5297. https://doi.org/10.1145/2858036.2858288 · DOI · Paper page
- Sonja Rümelin, Peter Siegl, and Andreas Butz. 2013. Could You Please...? Investigating Cooperation In The Car. In Adjunct Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '13), Eindhoven, The Netherlands, October 2013. (AutomotiveUI '13).
- Baoshi Yan, Fuliang Weng, Z. Feng, F. Ratiu, M. Raya, Y. Meng, S. Varges, M. Purver, A. Lien, T. Scheideck, B. Raghunathan, F. Lin, Rohit Mishra, Brian Lathrop, Zhaoxia Zhang, Harry Bratt, and Stanley Peters. 2007. A Conversational In-car Dialog System. In Proceedings of Human Language Technologies: Demonstrations (NAACL-Demonstrations '07). Association for Computational Linguistics, Stroudsburg, PA, USA, 23- 24. http://dl.acm.org/citation.cfm?id=1614164.1614176
Cited by
Sorted by citations
Voice in Human–Agent Interaction: A Survey
Seaborn, K., Miyake, N. P., Pennefather, P., & Otake-Matsuura, M. (2022) · ACM Computing Surveys · doi:10.1145/3386867 · Cited by 249 · see citing works
Kühne, K., Fischer, M. H., & Zhou, Y. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.593732 · Cited by 123 · see citing works
Wang, Q., Saha, K., Gregori, E., Joyner, D., & Goel, A. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445645 · Cited by 120 · see citing works
Braun, M., Weber, F., & Alt, F. (2021) · ACM Computing Surveys · doi:10.1145/3460938 · Cited by 115 · see citing works
Self-citationVoice assistants and older people: some open issues
Sayago, S., Neves, B. B., & Cowan, B. R. (2019) · Proceedings of the 1st International Conference on Conversational User Interfaces · doi:10.1145/3342775.3342803 · Cited by 97 · see citing works
Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data
Wei, J., Kim, S., Jung, H., & Kim, Y.-H. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637364 · Cited by 84 · see citing works
Zargham, N., Reicherts, L., Bonfert, M., Voelkel, S. T., Schoening, J., Malaka, R., & Rogers, Y. (2022) · Proceedings of the 4th Conference on Conversational User Interfaces · doi:10.1145/3543829.3543834 · Cited by 84 · see citing works
Peng, Z., Guo, Q., Tsang, K. W., & Ma, X. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376695 · Cited by 81 · see citing works
Eliciting and Analysing Users’ Envisioned Dialogues with Perfect Voice Assistants
Volkel, S. T., Buschek, D., Eiband, M., Cowan, B. R., & Hussmann, H. (2021) · International Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445536 · Cited by 95 · see citing works
Ha, J., Jeon, H., Han, D. S., Seo, J., & Oh, C. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642472 · Cited by 76 · see citing works
A Systematic Review of Voice Assistant Usability: An ISO 9241–11 Approach
Dutsinma, F. L. I., Pal, D., Funilkul, S., & Chan, J. (2022) · SN Computer Science · doi:10.1007/s42979-022-01172-3 · Cited by 72 · see citing works
“I’d like an Explanation for That!”Exploring Reactions to Unexpected Autonomous Driving
Wiegand, G., Eiband, M., Haubelt, M., & Hußmann, H. (2020) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/3379503.3403554 · Cited by 71 · see citing works
Choice of Voices: A Large-Scale Evaluation of Text-to-Speech Voice Quality for Long-Form Content
Cambre, J., Colnago, J., Maddock, J., Tsai, J. Y., & Kaye, J. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376789 · Cited by 90 · see citing works
Völkel, S. T., Schoedel, R., Buschek, D., Stachl, C., Winterhalter, V., Bühner, M., & Hussmann, H. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376210 · Cited by 65 · see citing works
Kuhail, M. A., Thomas, J., Alramlawi, S., Shah, S. J. H., & Thornquist, E. (2022) · Informatics · doi:10.3390/informatics9040081 · Cited by 59 · see citing works
Measuring Voice UX Quantitatively: A Rapid Review
Seaborn, K., & Urakami, J. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411763.3451712 · Cited by 55 · see citing works
Völkel, S. T., Schödel, R., Buschek, D., Stachl, C., Winterhalter, V., Bühner, M., & Hußmann, H. (2020) · Alexandria (UniSG) (University of St.Gallen) · Cited by 55 · see citing works
Mou, Y., & Meng, X. (2023) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-10-2022-0869 · Cited by 52 · see citing works
Jansen, P., Colley, M., & Rukzio, E. (2022) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3534617 · Cited by 46 · see citing works
Jellyfish: Timely Inference Serving for Dynamic Edge Networks
Nigade, V., Bauszat, P., Bal, H. E., & Wang, L. (2022) · IEEE Real-Time Systems Symposium (RTSS) · doi:10.1109/rtss55097.2022.00032 · Cited by 44 · see citing works
A survey on privacy issues and solutions for Voice-controlled Digital Assistants
Acosta, L. H., & Reinhardt, D. (2021) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2021.101523 · Cited by 43 · see citing works
Metaphors in Voice User Interfaces: A Slippery Fish
Desai, S., & Twidale, M. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3609326 · Cited by 42 · see citing works
Zhang, L., Jiang, L., Washington, N. L., Liu, A. A., Shao, J., Fourney, A., Morris, M., & Findlater, L. (2021) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3449235 · Cited by 34 · see citing works
Cheng, P., Meng, F., Yao, J., & Wang, Y. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.883417 · Cited by 40 · see citing works
"It's small talk, jim, but not as we know it."
Large, D. R., Clark, L., Burnett, G., Harrington, K., Luton, J., Thomas, P., & Bennett, P. (2019) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3342775.3342789 · Cited by 37 · see citing works
User Perceptions of Extraversion in Chatbots after Repeated Use
Völkel, S. T., Schoedel, R., Kaya, L., & Mayer, S. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502058 · Cited by 37 · see citing works
Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes
Melumad, S., Hadi, R., Hildebrand, C., & Ward, A. F. (2020) · Customer Needs and Solutions · doi:10.1007/s40547-020-00107-4 · Cited by 36 · see citing works
Yoo, Y., Yang, M.-Y., Lee, S., Baek, H. W., & Kim, J. (2022) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2022.01.009 · Cited by 37 · see citing works
Rincón, C., Keyes, O., & Cath, C. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449206 · Cited by 33 · see citing works
A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures
Baughan, A., Wang, X., Liu, A., Mercurio, A., Chen, J., & Ma, X. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581152 · Cited by 32 · see citing works
“In addition, customizing a voice assistant’s personality to the user can lead to higher trust [7], while gender does not impact users’ trust in a voice assistant [59].”
BackgroundAylett, M. P., Sutton, S. J., & Vazquez-Alvarez, Y. (2019) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3342775.3342806 · Cited by 31 · see citing works
Riegler, A., Aksoy, B., Riener, A., & Holzmann, C. (2020) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3409120.3410654 · Cited by 31 · see citing works
Pias, S. B. H., Huang, R., Williamson, D. S., Kim, M., & Kapadia, A. C. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665545 · Cited by 30 · see citing works
Ringfort-Felner, R., Laschke, M., Sadeghian, S., & Hassenzahl, M. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3492852 · Cited by 30 · see citing works
InSS: An Intelligent Scheduling Orchestrator for Multi-GPU Inference With Spatio-Temporal Sharing
Han, Z., Zhou, R., Xu, C., Zeng, Y., & Zhang, R. (2024) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2024.3430063 · Cited by 28 · see citing works
What If Your Car Would Care? Exploring Use Cases For Affective Automotive User Interfaces
Braun, M., Li, J., Weber, F., Pfleging, B., Butz, A. M., & Alt, F. (2020) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/3379503.3403530 · Cited by 28 · see citing works
Self-citationIntegrating Generative Artificial Intelligence in Intelligent Vehicle Systems
Stappen, L., Dillmann, J., Striegel, S., Vögel, H.-J., Flores-Herr, N., & Schuller, B. W. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422003 · Cited by 28 · see citing works
Chin, J., Desai, S., Lin, S. (.-H., & Mejia, S. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637365 · Cited by 27 · see citing works
When Do Drivers Interact with In-Vehicle Well-being Interventions?
Koch, K., Mishra, V., Liu, S., Berger, T., Fleisch, E., Kotz, D. F., & Wortmann, F. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3448116 · Cited by 25 · see citing works
Wenzel, K., Devireddy, N., Davison, C., & Kaufman, G. F. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581357 · Cited by 26 · see citing works
Kokorelias, K., Grigorovich, A., Harris, M. T., Rehman, U., Ritchie, L., Levy, A., Denecke, K., & McMurray, J. (2024) · Journal of Medical Internet Research · doi:10.2196/57258 · Cited by 23 · see citing works
What If Conversational Agents Became Invisible?
Lee, S., Cho, M., & Lee, S. (2020) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3411840 · Cited by 24 · see citing works
Zargham, N., Alexandrovsky, D., Erich, J., Wenig, N., & Malaka, R. (2022) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3491101.3519843 · Cited by 24 · see citing works
FrownOnError: Interrupting Responses from Smart Speakers by Facial Expressions
Yan, Y.-K., Yu, C., Zheng, W., Tang, R., Xu, X. "., & Shi, Y.-C. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376810 · Cited by 29 · see citing works
"Hi! I am the Crowd Tasker" Crowdsourcing through Digital Voice Assistants
Hettiachchi, D., Sarsenbayeva, Z., Allison, F., van Berkel, N., Dingler, T., Marini, G., Kostakos, V., & Gonçalves, J. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376320 · Cited by 23 · see citing works
A Review of Subjective Scales Measuring the User Experience of Voice Assistants
Faruk, L. I. D., Babakerkhell, M. D., Mongkolnam, P., Chongsuphajaisiddhi, V., Funilkul, S., & Pal, D. (2024) · IEEE Access · doi:10.1109/access.2024.3358423 · Cited by 25 · see citing works
User Experience of Driver State Visualizations: A Look at Demographics and Personalities
Braun, M., Chadowitz, R., & Alt, F. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29390-1_9 · Cited by 23 · see citing works
Self-citationUsable and Acceptable Response Delays of Conversational Agents in Automotive User Interfaces
Funk, M., Cunningham, C., Kanver, D., Saikalis, C., & Pansare, R. (2020) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3409120.3410651 · Cited by 21 · see citing works
Kuhail, M. A., Bahja, M., Al-Shamaileh, O., Thomas, J., Alkazemi, A., & Negreiros, J. G. M. (2024) · IEEE Access · doi:10.1109/access.2024.3402977 · Cited by 24 · see citing works
Examining Humanness as a Metaphor to Design Voice User Interfaces
Desai, S., Dubiel, M., & Leiva, L. A. (2024) · ACM Conversational User Interfaces 2024 · doi:10.1145/3640794.3665535 · Cited by 21 · see citing works
Liu, J., Wan, F., Zou, J., & Zhang, J. (2023) · World Electric Vehicle Journal · doi:10.3390/wevj14030073 · Cited by 21 · see citing works
A Segment Level Approach to Speech Emotion Recognition Using Transfer Learning
Sahoo, S., Kumar, P., Raman, B., & Roy, P. P. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-41299-9_34 · Cited by 21 · see citing works
AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance
Wen, S., Ping, S., Wang, J., Liang, H., Xu, X., & Yan, Y. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642876 · Cited by 20 · see citing works
Age-Related Differences in Preferences for Using Voice Assistants
Gollasch, D., & Weber, G. (2021) · Mensch und Computer (MuC) · doi:10.1145/3473856.3473889 · Cited by 20 · see citing works
Voice User Interface: Literature review, challenges and future directions
Francis, R., Randriatsarafara, H. N., Hajalalaina, A. R., & Manda-Vy, R. N. (2021) · SYSTEM THEORY CONTROL AND COMPUTING JOURNAL · doi:10.52846/stccj.2021.1.2.26 · Cited by 19 · see citing works
Zhao, Y., Jiang, K., Yu, Z., & Huang, Z. (2024) · Cognition Technology & Work · doi:10.1007/s10111-024-00756-8 · Cited by 20 · see citing works
Funk, M., Tobisch, V., & Emfield, A. G. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376816 · Cited by 20 · see citing works
Phinnemore, R., Reza, M., Lewis, B., Mahadevan, K., Wang, B. K., Annett, M., & Wigdor, D. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581346 · Cited by 18 · see citing works
Khorsandi, P. M., Jones, L., Davoodnia, V., Lampen, T. J., Conrad, A., Etemad, A., & Nabil, S. (2023) · Designing Interactive Systems Conference · doi:10.1145/3563657.3595988 · Cited by 18 · see citing works
Speaking with My Screen Reader: Using Audio Fictions to Explore Conversational Access to Interfaces
Phutane, M., Jung, C., Chen, N., & Azenkot, S. (2023) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3597638.3608404 · Cited by 18 · see citing works
Feijóo-García, P. G., Wrenn, C., de Siqueira, A. G., Ghosh, R., Stuart, J., Yao, H., & Lok, B. C. L. (2024) · ACM Transactions on Applied Perception · doi:10.1145/3689822 · Cited by 18 · see citing works
Braun, M., & Alt, F. (2019) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3290607.3313051 · Cited by 18 · see citing works
Self-citationUsability Questionnaires to Evaluate Voice User Interfaces
Iñiguez-Carrillo, A. L., Gaytan-Lugo, L. S., García-Ruiz, M. Á., & Arellano, R. M. (2021) · IEEE Latin America Transactions · doi:10.1109/tla.2021.9468439 · Cited by 17 · see citing works
Emotionality in Task-Oriented Chatbots – The Effect of Emotion Expression on Chatbot Perception
Pezenka, I., Aunimo, L., Janous, G., & Dobrowsky, D. (2024) · Communication Studies · doi:10.1080/10510974.2024.2363259 · Cited by 19 · see citing works
Völkel, S., Meindl, S., & Hussmann, H. (2021) · International Conference on Conversational User Interfaces · doi:10.1145/3469595.3469605 · Cited by 19 · see citing works
Meck, A.-M., & Precht, L. (2021) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3409118.3475144 · Cited by 16 · see citing works
Koch, K., Tiefenbeck, V., Liu, S., Berger, T., Fleisch, E., & Wortmann, F. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3446865 · Cited by 15 · see citing works
Classifying Cognitive Load for a Proactive In-car Voice Assistant
Schmidt, M., Bhandare, O., Prabhune, A., Minker, W., & Werner, S. (2020) · IEEE International Conference on Big Data Computing Service and Applications (BigDataService) · doi:10.1109/bigdataservice49289.2020.00010 · Cited by 15 · see citing works
Park, D., & Namkung, K. (2021) · Applied Sciences · doi:10.3390/app112311147 · Cited by 14 · see citing works
Kim, H., Jung, I., & Lim, Y.-K. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533528 · Cited by 14 · see citing works
Nigade, V., Winder, R., Bal, H. E., & Wang, L. (2021) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3485730.3493446 · Cited by 13 · see citing works
Lin, G. E., Li, J. Y., Fazly, A., Pavlović, V., & Truong, K. N. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581006 · Cited by 13 · see citing works
Emotion-Aware Voice Assistants: Design, Implementation, and Preliminary Insights
Ma, Y., Zhang, Y., Bachinski, M., & Fjeld, M. (2023) · International Symposium of Chinese CHI (Chinese CHI) · doi:10.1145/3629606.3629665 · Cited by 13 · see citing works
Dealing with Input Uncertainty in Automotive Voice Assistants
Tobisch, V., Funk, M., & Emfield, A. G. (2020) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3409120.3410660 · Cited by 13 · see citing works
He, F., & Burns, C. M. (2022) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3543174.3546845 · Cited by 13 · see citing works
Audiovisual Affect Recognition for Autonomous Vehicles: Applications and Future Agendas
Karas, V., Schuller, D., & Schuller, B. W. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3333749 · Cited by 12 · see citing works
Identifying Personality Dimensions for Characters of Digital Agents
Braun, M., & Alt, F. (2020) · Human-computer interaction series · doi:10.1007/978-3-030-15954-2_8 · Cited by 12 · see citing works
Self-citationTodi, K., Leiva, L. A., Buschek, D., Tian, P., & Oulasvirta, A. (2021) · Designing Interactive Systems Conference · doi:10.1145/3461778.3462124 · Cited by 12 · see citing works
Frison, A.-K., Wintersberger, P., Oberhofer, A., & Riener, A. (2019) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3349263.3351312 · Cited by 12 · see citing works
Personalised Chats with Voice Assistants
Völkel, S. T., Kempf, P., & Hußmann, H. (2020) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3405755.3406156 · Cited by 12 · see citing works
How May I Interrupt? Linguistic-Driven Design Guidelines for Proactive in-Car Voice Assistants
Meck, A.-M., Draxler, C., & Vogt, T. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2266251 · Cited by 11 · see citing works
Ma, Y., Abdelrahman, Y., Petz, B., Drewes, H., Alt, F., Hußmann, H., & Butz, A. M. (2022) · Mensch und Computer (MuC) · doi:10.1145/3543758.3543776 · Cited by 11 · see citing works
Self-citationLet Me Ask You This: How Can a Voice Assistant Elicit Explicit User Feedback?
Xiao, Z., Mennicken, S., Huber, B., Shonkoff, A., & Thom, J. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479532 · Cited by 11 · see citing works
Hu, S., Yen, R., Yu, Z., Zhao, M., Seaborn, K., & Liu, C. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579591 · Cited by 10 · see citing works
'No, not that voice again!': Engaging Older Adults in Design of Anthropomorphic Voice Assistants
Pradhan, A., Erete, S. L., Chopra, S., Upadhyay, P., Sule, O., & Lazar, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3711039 · Cited by 12 · see citing works
Towards User-Centric Text-to-Text Generation: A Survey
Yang, D., & Flek, L. (2021) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-83527-9_1 · Cited by 10 · see citing works
Modeling and optimizing the voice assistant behavior in Virtual Reality
Buchta, K., Wojcik, P., Nakonieczny, K., Janicka, J., Gałuszka, D., Sterna, R., & Igraś-Cybulska, M. (2022) · IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct57072.2022.00086 · Cited by 10 · see citing works
Jung, I., Kim, H., & Lim, Y.-K. (2021) · Designing Interactive Systems Conference · doi:10.1145/3461778.3462082 · Cited by 9 · see citing works
Burggräf, P., Beyer, M., Ganser, J.-P., Adlon, T., Muller, K., Riess, C., Zollner, K., Sabmannshausen, T., & Kammerer, V. (2022) · IEEE Access · doi:10.1109/access.2022.3174592 · Cited by 9 · see citing works
Hao, P., Wang, M., Wang, J., & Zhu, Q. (2024) · IEEE Access · doi:10.1109/access.2024.3492207 · Cited by 10 · see citing works
Tickling Proactivity: Exploring the Use of Humor in Proactive Voice Assistants
Zargham, N., Reicherts, L., Avanesi, V., Rogers, Y., & Malaka, R. (2023) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3626705.3627777 · Cited by 9 · see citing works
Enabling Hands-Free Voice Assistant Activation on Earphones
Chen, T., Yang, Y., Qiu, C., Fan, X., Guo, X., & Shangguan, L. (2024) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3643832.3661890 · Cited by 9 · see citing works
Kim, J., & Heo, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77392-2_12 · Cited by 9 · see citing works
Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant
Wu, D., & Huang, Y. (2021) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.464 · Cited by 10 · see citing works
Effects of Speaking Rate on Speech and Silent Speech Recognition
Pandey, L., & Arif, A. S. (2022) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3491101.3519611 · Cited by 9 · see citing works
Nonbinary Voices for Digital Assistants—An Investigation of User Perceptions and Gender Stereotypes
Längle, S. T., Schlögl, S., Ecker, A., van Kooten, W. S. M. T., & Spieß, T. (2024) · Robotics · doi:10.3390/robotics13080111 · Cited by 8 · see citing works
Voice Commerce: Anthropomorphism Using Voice Assistants
Nguyen, H. S., Mladenow, A., Strauß, C., & Auer‐Srnka, K. J. (2021) · International Conference on Information Integration and Web-based Applications & Services (iiWAS) · doi:10.1145/3487664.3487724 · Cited by 9 · see citing works
Body Language for VUIs: Exploring Gestures to Enhance Interactions with Voice User Interfaces
Wu, L., Lafreniere, B., Grossman, T., White, T., & Santosa, S. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3660691 · Cited by 7 · see citing works
Shin, J., Ko, H., Bae, S. W., & Kim, J. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2441530 · Cited by 7 · see citing works
Evoking trust in smart voice assistants
Wetzels, R. W. H., Wetzels, M. G. M., Grewal, D., & Doek, B. (2025) · Journal of service management · doi:10.1108/josm-06-2024-0275 · Cited by 7 · see citing works
- Authors
- Braun, M., Mainz, A., Chadowitz, R., Pfleging, B., & Alt, F.
- Affiliations
- BMW (Germany) (DE)
- Ludwig-Maximilians-Universität München (DE)
- Universität der Bundeswehr München (DE)
- Venue
- Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2019-05-02
- Pages
- 1-11
- OpenAlex
- W2941327948
- Cited by
- 182
- References
- 47
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 28 · 2023: 32 · 2022: 24 · 2021: 33 · 2020: 25 · 2019: 7
- FWCI
- 8.51
- Type
- conference paper
- Language
- en
- Open access
- green
- research.tue.nl
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- TU/e Research Portal (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- likeability, trust, user satisfaction
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