HUMAN PSYCHE CREATION BY APPLICATION OF NATURAL LANGUAGE PROCESSING TECHNOLOGIES

Tatarnikova T.M., Bogdanov P.Yu. Human psyche creation by application of natural language processing technologies. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2021, vol. 21, no. 1, pp. 85–91 (in Russian). doi: 10.17586/2226-1494-2021-21-1-85-91

Subject of Research. The paper proposes a solution for the human psyche automatic creation based on his speech behavior analysis. It is shown that messages in social networks, instant messengers and chats can be used to form a training data set, both in the format of text messages and audio and video calls. The functions of the psychological type classifier constituents are revealed by the human speech behavior. A comparison is made between multiclass and binary classification based on the loss function minimization. Methods. The human psyche corresponded to the Myers-Briggs type indicator, which subsumes a person to one of 16 types. The technologies of Text Mining for natural language processing and a deep learning model for speech processing were used. The data set for training and testing was formed by recordings of people’s speech translated into text format. Class labels were formed by the content of a text parameters vector, which is a dictionary of frequently encountered words. A deep learning algorithm was used for the human psyche automatic creation and was based on recurrent neural networks of the Long Short-Term Memory type. The algorithm was tested both for multiclass and binary classification. The objectivity of the proposed approach to a human psyche creation was ensured by the variety of content created by a person at various time in accordance with life situations, profession, hobbies and other circumstances. Main Results. A new approach to the automatic human psyche creation is proposed, based on the binary classification and a deep learning model. The convergence of the binary classification results with the test set of the speech behavior of various people is demonstrated. The Long Short-Term Memory network application in binary classification makes it possible to achieve an accuracy equal to 83 % of the psychological type correct determination and reduce the losses to 25 %. Practical Relevance. Automatic human psyche creation based on his speech behavior enables various specialists (such as psychologists, sociologists, human resources staff members) to make decisions when working with a specific person. Analysis of a human personal qualities by his speech behavior is software-implemented.

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