Identification of speech characteristics to distinguish human personality of introversive and extroversive male groups

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dc.contributor.authorPark, Jangwoon
dc.contributor.authorLee, Sinae
dc.contributor.authorBrotherton, Kimberly
dc.contributor.authorUm, Dugan
dc.contributor.authorPark, Jaehyun
dc.creator.orcidhttps://orcid.org/0000-0002-5264-6941en_US
dc.creator.orcidhttps://orcid.org/0000-0003-4999-8345en_US
dc.creator.orcidhttps://orcid.org/0000-0002-5264-6941
dc.creator.orcidhttps://orcid.org/0000-0003-4999-8345
dc.creator.orcidhttps://orcid.org/0000-0002-5264-6941
dc.creator.orcidhttps://orcid.org/0000-0003-4999-8345https://orcid.org/0000-0002-5264-6941
dc.creator.orcidhttps://orcid.org/0000-0003-4999-8345
dc.date.accessioned2021-10-26T20:12:44Z
dc.date.available2021-10-26T20:12:44Z
dc.date.issued2020-03-23
dc.description.abstractAccording 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.en_US
dc.description.abstractAccording 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.
dc.identifier.citationPark, J., Lee, S., Brotherton, K., Um, D. and Park, J., 2020. Identification of speech characteristics to distinguish human personality of introversive and extroversive male groups. International journal of environmental research and public health, 17(6), p.2125.en_US
dc.identifier.citationPark, J., Lee, S., Brotherton, K., Um, D. and Park, J., 2020. Identification of speech characteristics to distinguish human personality of introversive and extroversive male groups. International journal of environmental research and public health, 17(6), p.2125.
dc.identifier.doihttps://doi.org/10.3390/ijerph17062125
dc.identifier.urihttps://hdl.handle.net/1969.6/89864
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherMDPIen_US
dc.publisherMDPI
dc.rightsAttribution 4.0 International*
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectpersonalityen_US
dc.subjectspeechen_US
dc.subjectreaction timeen_US
dc.subjectsound pressureen_US
dc.subjectpitchen_US
dc.subjectlinguisticsen_US
dc.subjecthuman-robot interactionen_US
dc.subjectuser experienceen_US
dc.subjectusabilityen_US
dc.subjectpersonality
dc.subjectspeech
dc.subjectreaction time
dc.subjectsound pressure
dc.subjectpitch
dc.subjectlinguistics
dc.subjecthuman-robot interaction
dc.subjectuser experience
dc.subjectusability
dc.titleIdentification of speech characteristics to distinguish human personality of introversive and extroversive male groupsen_US
dc.titleIdentification of speech characteristics to distinguish human personality of introversive and extroversive male groups
dc.typeArticleen_US
dc.typeArticle

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