Research of speech genres in artificial intelligence applications (identification of cognitive-speech actions forming a genre form)
| Autor: | Natalya V. Chudova, Dmitry A. Devyatkin, Vladimir A. Salimovsky, Liudmila A. Kadzhaya, Valery A. Mishlanov, Control' Ras |
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| Jazyk: | ruština |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Жанры речи, Vol 31, Iss 3, Pp 170-180 (2021) |
| ISSN: | 2311-0759 2311-0740 |
| Popis: | The paper proves that speech genres as forms of text production and interpretation claim to be one of the main objects of formal linguistic analysis in comprehensive papers on cognitive modeling – an intensively developing trend of artificial intelligence. Understanding a speech genre as a form of spiritual socio-cultural activity (artistic, scientific, political, ideological, etc.) at the level of its objectification through a system of speech actions in the text as a communication unit allows to describe the systems of speech genres in various spheres of communication. The authors analyze speech genres which objectify the main stages of an academic theoretical research. By means of artificial intelligence, the research solves the problem of recognition of the speaker’s intentions while performing cognitive-speech actions forming the genre form of a text. It contributes to the development of the fundamental problem of “understanding” the meaning of an utterance by a machine. The research is based on the interdisciplinary complex method of text analysis. In terms of software implementation, the offered approach obtains a small set of high-level linguistic features of the clauses with the templates and then trains classifiers on these features. In order to create templates, the authors carry out linguistic and psychological analysis that deals with identifying markers of cognitive and speech actions as accurately as possible in accordance with the standards of perception. In the course of our study, the authors have obtained high indexes of cognitive and speech action identification, ranging from 0.78 to 0.99. |
| Databáze: | OpenAIRE |
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