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

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.