Abstract
There is an increasing need for human interaction to improve with electronics in this digital age. Socially assistive robot (SAR) interactions with the elderly and youth can improve the quality of these individuals’ lives in terms of friendships. Since humans are emotional creatures and respond more agreeably to similar personality types, robots need to be designed and programmed in a more intuitive way to capture and match the users’ personal characteristics to maximize human-machine friendships. The present study is intended to identify significant vocal features associated with a human’s personality type (introverted vs. extroverted), in a digital signal processing environment, and use vocal traits for characterization. The voices of 28 university students (14 introverted and 14 extroverted) were recorded when each verbally responded to the Walk-in-the-Woods questionnaire. Then, the response time for the first question for each participant was extracted. Statistical analyses were employed to test significances of each measure for the two personality groups (introverted vs. extroverted).
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Brotherton, K., Park, J., Um, D., Mehrubeoglu, M. (2020). Identification of the Relationships Between a Vocal Attribute and a Personality. In: Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. AHFE 2019. Advances in Intelligent Systems and Computing, vol 962. Springer, Cham. https://doi.org/10.1007/978-3-030-20467-9_15
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DOI: https://doi.org/10.1007/978-3-030-20467-9_15
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