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Improving automotive safety by pairing driver emotion and car voice emotion
Abstract
This study examines whether characteristics of a car voice can affect driver performance and affect. In a 2 (driver emotion: happy or upset) x 2 (car voice emotion: energetic vs. subdued) experimental study, participants (N=40) had emotion induced through watching one of two sets of 5-minute video clips. Participants then spent 20 minutes in a driving simulator where a voice in the car spoke 36 questions (e.g., "How do you think that the car is performing?") and comments ("My favorite part of this drive is the lighthouse.") in either an energetic or subdued voice. Participants were invited to interact with the car voice. When user emotion matched car voice emotion (happy/energetic and upset/subdued), drivers had fewer accidents, attended more to the road (actual and perceived), and spoke more to the car. Implications for car design and voice user interface design are discussed.
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“Nass et al. (2005) found that matching a driver's emotion to a car's voicebased emotion led to better performance in a driving simulator.”
From Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm (2020) · cites this paper as Nass et al., 2005
Citations
Cites
Picard, R. W. (1997) · MIT Press · doi:10.7551/mitpress/1140.001.0001 · Cited by 7,382
Handbook of personality theory and research
Wilson, G. (1991) · Personality and Individual Differences · doi:10.1016/0191-8869(91)90043-b · Cited by 3,562
Positive affect and decision making.
Isen, A. M. (1993) · Medical Entomology and Zoology · Cited by 1,135
(2005) · Cited by 505
Self-citationWired for Speech: How Voice Activates and Advances the Human-Computer Relationship
Callaway, C. B., & Sima’an, K. (2006) · Computational Linguistics · doi:10.1162/coli.2006.32.3.451 · Cited by 407
EMOTION IN HUMAN-COMPUTER INTERACTION
Brave, S., & Nass, C. (2007) · CRC Press eBooks · doi:10.1201/9781410615862-13 · Cited by 348
Self-citationEmotion and emotion regulation.
Gross, J. J. (1999) · Cited by 242
A Bio-Informational Theory of Emotion: Motion and Image Size Effects on Viewers
Detenber, B. H., & Reeves, B. B. (1996) · Journal of Communication · doi:10.1111/j.1460-2466.1996.tb01489.x · Cited by 212
Handbook of human-computer interaction
(1990) · Information and Software Technology · doi:10.1016/0950-5849(90)90123-9 · Cited by 122
Road rage: a domain for psychological intervention?
Galovski, T. E., & Blanchard, E. B. (2003) · Aggression and Violent Behavior · doi:10.1016/s1359-1789(02)00118-0 · Cited by 103
Flagged first, then by citations
Research works printed but not linked: 2
- Izard , C.E. Patterns of emotions . Academic Press , New York , 1972 . Izard, C.E. Patterns of emotions. Academic Press, New York, 1972.
- 10.5555/265013 · DOI
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Sorted by citations
Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm
Gambino, A., Fox, J., & Ratan, R. (2020) · Human-Machine Communication · doi:10.30658/hmc.1.5 · Cited by 626
“…on a screen, CASA retained its predictive validity in a wide range of contexts, including anthropomorphic interfaces (E. J. Lee, 2010b), embodied agents (Hoffmann et al., 2009; K. M. Lee et al., 2006), mobile phones (Carolus et al., 2018), and voice-based navigational systems (Nass et al., 2005).”
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Predicting information technology usage in the car
Osswald, S., Wurhofer, D., Trösterer, S., Beck, E., & Tscheligi, M. (2012) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/2390256.2390264 · Cited by 261
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
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Effects of specific emotions on subjective judgment, driving performance, and perceived workload
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Park, C. Y., Cha, N., Kang, S., Kim, A., Khandoker, A. H., Hadjileontiadis, L., Oh, A., Jeong, Y., & Lee, U. (2020) · Scientific Data · doi:10.1038/s41597-020-00630-y · Cited by 205
Emotion on the Road—Necessity, Acceptance, and Feasibility of Affective Computing in the Car
Eyben, F., Wöllmer, M., Poitschke, T., Schuller, B. W., Blaschke, C., Färber, B., & Nguyen-Thien, N. (2010) · Advances in Human-Computer Interaction · doi:10.1155/2010/263593 · Cited by 183
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Explanations and Expectations: Trust Building in Automated Vehicles
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Naqvi, R. A., Arsalan, M., Rehman, A., Rehman, A. U., Loh, W.-K., & Paul, A. (2020) · Remote Sensing · doi:10.3390/rs12030587 · Cited by 76
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Lee, K.-W., Yoon, H. S., Song, J.-M., & Park, K. (2018) · Italian National Conference on Sensors · doi:10.3390/s18040957 · Cited by 70
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Joo, Y. K., & Lee, J.-E. R. (2014) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2013.0157 · Cited by 24
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Atmaja, B. T., & Akagi, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.02355 · Cited by 20
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Wang, J., Liu, Y., Yue, T., Wang, C., Mao, J., Wang, Y., & You, F. (2021) · Sensors · doi:10.3390/s21175722 · Cited by 21
Metadata
- Authors
- Nass, C., Jonsson, I.-M., Harris, H., Reaves, B., Endo, J., Brave, S., & Takayama, L.
- Affiliations
- Stanford University (US)
- Toyota Information Technology Center, Palo Alto, CA
- Venue
- CHI '05 Extended Abstracts on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2005-04-02
- Pages
- 1973-1976
- OpenAlex
- W2164809575
- Cited by
- 249
- References
- 10
- Citations by year
- 2026: 6 · 2025: 18 · 2024: 17 · 2023: 8 · 2022: 17 · 2021: 25 · 2020: 18 · 2019: 26 · 2018: 14 · 2017: 15 · 2016: 5 · 2015: 11 · 2014: 16 · 2013: 7 · 2012: 7
- FWCI
- 8.52
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- driver emotions, voice user interface, driving performance, road safety, driver attention, tone of voice, in-vehicle interaction, driver-vehicle interaction
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