Browse > Article
http://dx.doi.org/10.14695/KJSOS.2022.25.4.129

Investigating the Relationship Between Vehicle Front Images and Voice Assistants  

Min-Jung Park (한국과학기술원 산업디자인학과)
So-Yeong Min (한국과학기술원 산업디자인학과)
Tae-Su Kim (한국과학기술원 산업디자인학과 )
Hyeon-Jeong Suk (한국과학기술원 산업디자인학과 )
Publication Information
Science of Emotion and Sensibility / v.25, no.4, 2022 , pp. 129-138 More about this Journal
Abstract
In the context of the increasing applications of voice assistants in vehicles, we focused on the association between the visual appeal of the cars and the acoustic characteristics of the voice assistants. This study aimed to investigate the relationship between the visual appeal of the vehicle and the voice assistant based on their emotional characteristics. A total of 15 adjectives were used to assess the emotional characteristics of 12 types of cars and six types of voices. An online interview was carried out, instructing participants to match three adjectives with the presented car images or voices. This was followed with a brief interview to allow the participants to reflect on the adjective matches. Based on the assessments, we performed principal component analysis (PCA) to determine factors. We aimed to deploy the cars and voices and analyze the patterns of clustering. The PCA analysis revealed two factors profiled as "Light-Heavy" and "Comfortable-Radical." Both car and voice stimuli were deployed in a two-dimensional space showing the internal relationship within and between the two substances. Based on the coordination data, a hierarchical cluster grouped the 18 stimuli into four groups labeled as challenge, elegance, majesty, and vigor. This study identified two latent factors describing the emotional characteristics of both car images and voice types clustered into four groups based on their emotional characteristics. The coherent matches between car style and voice type are expected to address the design concept more successfully.
Keywords
Affective User Experience; Style Relationship; Vehicle Image; Voice Assistance;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Peissner, M., Doebler, V., & Metze, F. (2011). Can voice interaction help reducing the level of distraction and prevent accidents. Metastudy Driver Distraction Voice Interaction, 24(5).
2 Ranscombe, C., Hicks, B., Mullineux, G., & Singh, B. (2012). Visually decomposing vehicle images: Exploring the influence of different aesthetic features on consumer perception of brand. Design Studies, 33(4), 319-341. DOI: 10.1016/j.destud.2011.06.006   DOI
3 SANO, S. (2010). Facial expressions in car design. DOI: 10.5281/zenodo.2605681   DOI
4 Sodnik, J., Dicke, C., Tomazic, S., & Billinghurst, M. (2008). A user study of auditory versus visual interfaces for use while driving. International Journal of Human-Computer Studies, 66(5), 318-332. DOI: 10.1016/ j.ijhcs.2007.11.001   DOI
5 Tewari, A., Khan, S., Krishnan, A., Rauth, T., & Singh, J. (2018). Smart driver assistant.2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), 1127-1131. DOI: 10.1109/ICECA.2018.8474760   DOI
6 Waytz, A., Heafner, J., & Epley, N. (2014). The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle. Journal of Experimental Social Psychology, 52, 113-117. DOI: 10.1016/j.jesp.2014.01.005   DOI
7 Yoo, Y., Yang, M.-y., Lee, S., Baek, H., & Kim, J. (2022). The effect of the dominance of an in-vehicle agent's voice on driver situation awareness, emotion regulation, and trust: A simulated lab study of manual and automated driving. Transportation Research Part F: Traffic Psychology and Behaviour, 86, 33-47. DOI: 10.1016/j.trf.2022.01.009   DOI
8 Benz, M. (2019). Mbux [(Accessed on 01/14/2022)]. Retrieved from %5Curl%7Bhttps://www.mercedes-benz.co.kr/passengercars/mercedes-benz-cars/models/a-class/hatchback-w177/comfort/model-year-update-v2.module.html%7D
9 BMW. (2019). Bmw intelligent personal assistant. [(Accessed on 01/14/2022)].
10 Braun, M., Mainz, A., Chadowitz, R., Pfleging, B., & Alt, F. (2019). At your service: Designing voice assistant personalities to improve automotive user interfaces. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-11. DOI: 10.1016/S0165-1838(96)00108-7   DOI
11 Cambre, J., & Kulkarni, C. (2019). One voice fits all? social implications and research challenges of designing voices for smart devices. Proceedings of the ACM on human-computer interaction, 3 (CSCW), 1-19. DOI: 10.1145/3359325   DOI
12 Chae, H. S., Hong, J. Y., Jeon, M. H., & Han, K. H. (2007). A study on voice user interface for domestic appliance, Science of Emotion & Sensibility, 10(1), 55-68.
13 Chae, H. S., Hong, J. Y., Lee, J. H., Jeon, M. H., & Han, K. H. (2007). A study on voice user interface for domestic appliance. Science of Emotion & Sensibility, 10(1), 55-68
14 Choi, Y. (2008). A study on the predictions of impression evaluation of speech voice. Journal of Speech and Hearing Disorders, 17(1), 123-145. DOI: 10.15724/jslhd.2008.17.1.007   DOI
15 Easwara Moorthy, A., & Vu, K.-P. L. (2015). Privacy concerns for use of voice activated personal assistant in the public space. International Journal of Human-Computer Interaction, 31(4), 307-335. DOI: 10.1080/10447318.2014.986642   DOI
16 Jindo, T., & Hirasago, K. (1997). Application studies to car interior of kansei engineering. International Journal of Industrial Ergonomics, 19(2), 105-114. DOI: 10.1016/S0169-8141(96)00007-8   DOI
17 Eric, T., Ivanovic, S., Milivojsa, S., Matic, M., & Smiljkovic, N. (2017, September). Voice control for smart home automation: Evaluation of approaches and possible architectures. In 2017 IEEE 7th International Conference on Consumer Electronics-Berlin (ICCE-Berlin) (pp. 140-142). IEEE. DOI: 10.1109/ICCE-Berlin.2017.8210613   DOI
18 Forster, Y., Naujoks, F., & Neukum, A. (2017). Increasing anthropomorphism and trust in automated driving functions by adding speech output. 2017 IEEE intelligent vehicles symposium (IV), 365-372. DOI: 10.1109/IVS.2017.7995746   DOI
19 Hoback, A. S. (2018). Pareidolia and perception of anger in vehicle styles: Survey results. International Journal of Psychological and Behavioral Sciences, 12(8), 1049-1055. DOI: 10.5281/zenodo.1340556   DOI
20 Kim, G., & Kim, J.-S. (2011). The effect of attitude type and preference about car design on eye movement. Korean Journal of Consumer and Advertising Psychology, 12(2), 379-404. DOI: 10.21074/kjlcap.2011.12.2.379   DOI
21 Kim, J., & Han, K. (2014). Emotion changed by headlamp design factors of frontal vehicle design. HCI Korea 2014, 683-686.
22 Lee, K., & Choi, K.-W. (2008). An observation on expression factors in automotive frontal exterior designs. Archives of Design Research, 21(4), 35-45.
23 Lee, S., Kim, S., & Lee, S. (2019). "what does your agent look like?" a drawing study to understand users' perceived persona of conversational agent. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 1-6. DOI: 10.1145/3290607.3312796   DOI
24 Matsuoka, T., Kanai, H., Tsuji, H., Shinya, T., & Nsihimatsu, T. (2008). Predicting texture image of covering fabric for car seat by physical properties. Journal of Textile Engineering, 54(3), 63-74. DOI: 10.4188/jte.54.63   DOI
25 Liem, A., Abidin, S., & Warell, A. (2009). Designers' perceptions of typical characteristics of form treatment in automobile styling. 5th International Workshop on Design & Semantics of Form and Movement, DesForm.
26 Lopatovska, I., Rink, K., Knight, I., Raines, K., Cosenza, K., Williams, H., Sorsche, P., Hirsch, D., Li, Q., & Martinez, A. (2019). Talk to me: Exploring user interactions with the amazon alexa. Journal of Librarianship and Information Science, 51(4), 984-997. DOI: 10.1177%2F0961000618759414   DOI
27 Lugano, G. (2017). Virtual assistants and self-driving cars. 2017 15th International Conference on ITS Telecommunications (ITST), 1-5. DOI: 10.1109/ITST.2017.7972192   DOI
28 Moore, R. K. (2017). Appropriate voices for artefacts: Some key insights. 1st International workshop on vocal interactivity in-and-between humans, animals and robots.
29 Nafari, M., & Weaver, C. (2013). Augmenting visualization with natural language translation of interaction: A usability study. Computer Graphics Forum, 32(3pt4), 391-400. DOI: 10.1111/cgf.12126   DOI
30 Nasirian, F., Ahmadian, M., & Lee, O.-K. D. (2017). Ai-based voice assistant systems: Evaluating from the interaction and trust perspectives.
31 Nass, C., Jonsson, I.-M., Harris, H., Reaves, B., Endo, J., Brave, S., & Takayama, L. (2005). Improving automotive safety by pairing driver emotion and car voice emotion. CHI'05 extended abstracts on Human factors in computing systems, 1973-1976. DOI: 10.1145/1056808.1057070   DOI