TY - GEN

T1 - Mental Chronometry of Speech Comprehension and Data Science Approach to Intelligent Database in Cognitive Science

AU - Lebedkin, Dmitri A.

AU - Saprygin, Alexander E.

AU - Vergunov, Evgeny G.

AU - Savostyanov, Alexander N.

N1 - Funding Information: Financial support: The study was supported by grant № 22-15-00142 of Russian Science Foundation. Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - One of the key problems of modern cognitive research is the development of methods for unbiased assessment of people's personality traits. The methods of personality questionnaires traditional for psychology in some cases give inadequate assessments that arise as a result of the respondent's unwillingness to truthfully answer the test questions, or his unconscious distortion of self-esteem. As an alternative, methods of implicit assessment of personality traits have been developed. One of these methods is the analysis of the characteristics of a person's response to the emotionally colored phrases. In this study, we analyzed behavioral responses under conditions of recognition of negative emotional sentences describing aggression either of the participant or others. We have proposed a statistical analysis model that makes it possible to evaluate the personal specificity of a person's response to the appearance of such sentences, taking into account both the semantic and grammatical features of verbal stimuli. It was shown that the usage of Data Science for processing behavioral data in terms of implicit recognition of speech emotions can be used to compile Intelligent Databases that reflect the psychological personality traits of survey participants.

AB - One of the key problems of modern cognitive research is the development of methods for unbiased assessment of people's personality traits. The methods of personality questionnaires traditional for psychology in some cases give inadequate assessments that arise as a result of the respondent's unwillingness to truthfully answer the test questions, or his unconscious distortion of self-esteem. As an alternative, methods of implicit assessment of personality traits have been developed. One of these methods is the analysis of the characteristics of a person's response to the emotionally colored phrases. In this study, we analyzed behavioral responses under conditions of recognition of negative emotional sentences describing aggression either of the participant or others. We have proposed a statistical analysis model that makes it possible to evaluate the personal specificity of a person's response to the appearance of such sentences, taking into account both the semantic and grammatical features of verbal stimuli. It was shown that the usage of Data Science for processing behavioral data in terms of implicit recognition of speech emotions can be used to compile Intelligent Databases that reflect the psychological personality traits of survey participants.

KW - data science

KW - intelligent database

KW - mental chronometry

KW - permutation approach

KW - personality theory

KW - speech comprehension task

UR - http://www.scopus.com/inward/record.url?scp=85137369481&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/fbb4ff13-f55d-3cb0-a166-d54036b9ab10/

U2 - 10.1109/EDM55285.2022.9855030

DO - 10.1109/EDM55285.2022.9855030

M3 - Conference contribution

AN - SCOPUS:85137369481

SN - 9781665498043

T3 - International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM

SP - 519

EP - 524

BT - Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

PB - IEEE Computer Society

T2 - 23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

Y2 - 30 June 2022 through 4 July 2022

ER -