Abstract
According to the similarity-attraction theory, humans respond more positively to people who are similar in personality. This observation also holds true between humans and robots, as shown by recent studies that examined human-robot interactions. Thus, it would be conducive for robots to be able to capture the user personality and adjust the interactional patterns accordingly. The present study is intended to identify significant speech characteristics such as sound and lexical features between the two different personality groups (introverts vs. extroverts), so that a robot can distinguish a user’s personality by observing specific speech characteristics. Twenty-four male participants took the Myers-Briggs Type Indicator (MBTI) test for personality screening. The speech data of those participants (identified as 12 introvertive males and 12 extroversive males through the MBTI test) were recorded while they were verbally responding to the eight Walk-in-the-Wood questions. After that, speech, sound, and lexical features were extracted. Averaged reaction time (1.200 s for introversive and 0.762 s for extroversive; p = 0.01) and total reaction time (9.39 s for introversive and 6.10 s for extroversive; p = 0.008) showed significant differences between the two groups. However, averaged pitch frequency, sound power, and lexical features did not show significant differences between the two groups. A binary logistic regression developed to classify two different personalities showed 70.8% of classification accuracy. Significant speech features between introversive and extroversive individuals have been identified, and a personality classification model has been developed. The identified features would be applicable for designing or programming a social robot to promote human-robot interaction by matching the robot’s behaviors toward a user’s personality estimated.
Highlights
The digital footprints people leave on online sites can be vigorously used to customize advertisement for each individual while they are online
The test is taken in a questionnaire format, and identifier letters are assigned to the 16 personality types, where eight types belong to introverts, and the other eight types belong to extroverts
No statistical significance was observed in the total speech time (p = 0.163), averaged pitch frequency (p = 0.585), and averaged sound power (p = 0.526)
Summary
The digital footprints people leave on online sites can be vigorously used to customize advertisement for each individual while they are online. A recent study by Dr Sandra Matz at Columbia Business School demonstrated that extroverted individual preferred simple images and images that featured people, while more open-minded individuals favored pictures with no people and with cool colors like blue and black [1]. Capturing a customer’s personality and emotions will eventually shape the advertisement industry to a level unprecedented so far. The more the users use the robot or AI devices, the better the chance of success of the advertisement. Res. Public Health 2020, 17, 2125; doi:10.3390/ijerph17062125 www.mdpi.com/journal/ijerph
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Environmental Research and Public Health
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.