The article is devoted to the study of the speech cliché “Everything will be fine” in modern communicative space and to the analysis of the ability of neural network models to interpret its emotional and pragmatic meaning. The relevance of the research is determined by the active spread of formulaic speech patterns in digital communication, as well as by the insufficient scientific development of the problem of speech cliché recognition by artificial intelligence systems. The aim of the study is to identify the functional features of the cliché “Everything will be fine” in various contexts and to evaluate the ability of modern neural network models to recognize its semantic and emotional nuances. The research is based on a comprehensive linguistic approach, including semantic, phonetic, and morphological analysis of the cliché, as well as a comparative analysis of interpretations produced by the neural network models ChatGPT, Mistral AI, DeepSeek, and Alice. In addition, methods of contextual analysis, comparison, and interpretation of speech situations were applied. The results of the study demonstrate that modern neural network models show a limited ability to perform deep pragmatic analysis of speech clichés, often relying on literal interpretation and experiencing difficulties in distinguishing irony, sarcasm, and politely indifferent emotional coloring. It is concluded that increasing the scale and computational power of language models does not lead to a fundamental improvement in recognizing the communicative intention of the speaker. The theoretical significance of the study lies in expanding scientific understanding of the functioning of speech clichés in modern communication and the peculiarities of their interpretation by artificial intelligence systems. The practical significance of the research consists in the possibility of applying the obtained results to the development and improvement of natural language processing systems aimed at more accurate recognition of contextual and emotional characteristics of speech.
speech cliché, emotional coloring, artificial intelligence, neural network models, “Everything will be fine”
1. Vse budet horosho. [Elektronnyy resurs] / Nacional'nyy korpus russkogo yazyka // URL:https://ruscorpora.ru/results?search=ClEqGwoICAAQChgyIAoQBSAAQAVqBDAuOTV4AKABATICCAE6AQFCKwopCicKA3JlcRIgCh7QstGB0ZEg0LHRg9C00LXRgiDRhdC%252B0Y DQvtGI0L4%253D
2. Gavaeva N.N., Shevchenko O.A. Klishe kak funkcional'naya edinica teksta (k probleme termina i ponyatiya) [Elektronnyy resurs] / StudFiles // URL: https://studfile.net/preview/358222/page:9/
3. Kakoy ChatGPT vybrat' v 2025 godu? Podrobnyy razbor vseh modeley. [Elektronnyy resurs] / Habr // URL: https://habr.com/ru/companies/bothub/articles/887988/
4. Lingvisticheskie mehanizmy social'nogo vzaimodeystviya: Grammatika – Semantika – Pragmatika [Elektronnyy resurs] / Institut Pushkina // URL: https://www.youtube.com/live/kHmFmDEqTDw?si=A60oU7qQnoGs6q9h
5. Mistral Large 3. [Elektronnyy resurs] / Mistral AI // URL: https://mistral.ai/models
6. Testiruem YandexGPT-5-Pro. Kogda hotelos' byt' ChatGPT, no v dushe vse esche Alisa. [Elektronnyy resurs] / Habr // URL: https://habr.com/ru/companies/bothub/articles/893128/
7. Chto takoe DeepSeek i na chto sposobna kitayskaya neyroset', iz-za kotoroy OpenAI snizil cenu na ChatGPT. [Elektronnyy resurs] / Habr // URL: https://habr.com/ru/companies/x-com/articles/878218/
