речевая системность

The paper examines a large language model (LLM) to recognize speech genres. Although artificial neural networks are effectively utilized in many important fields, they, however, have a serious drawback. The mechanism of their functioning is hidden from researchers; therefore, the results of their use do not get explanation. The purpose of the study is to reveal the basic mechanisms of functioning of the linguistic model LLM (Transformer) and thereby ensure the interpretability of the data it provides.

This is the second article in a cycle on the connection between genre studies and linguistics. The previous article discussed the question “What have genre studies given to linguistics?” This article focuses on linguistic methods used in speech genres theory: more traditional for linguistics, starting with the descriptive method and its later varieties – structural – and less traditional (component analysis, the method of immediate constituents, the generative method, the method of describing external and deep content structures, the method of semantic fields).

This paper presents the proposition that a speech genre as a relatively stable form of mental activity implemented in the text can be considered an object of cognitive modeling. The article contains a review of discourse concepts used in the computer text analysis.