LARGE LANGUAGE MODELS AND MACHINE TRANSLATION
Maryana Tomenchuk, Kseniia Popovych · Věda a perspektivy · 2024
Our article deals with linguistic peculiarities of machine translation provided by large language models, focusing on its lexical, semantic and syntactic aspects.Due to the fact that large language models are a rapidly developing notion of 21 st century, the ability to understand their architecture and relation to linguistics and translation in particular is of a great importance.The study is based on the investigation of ChatGPT -a very efficient large language model, which is capable of producing human-like outputs when provided with a certain task.Through the analysis of ChatGPT-responses, we further investigate its ability to convey linguistic meaning in different aspects of a language.The main purpose of our investigation is to analyze linguistic notions from different subfields, such as syntax, lexis and semantics by reviewing the translations of GPT from target to source language.In our case, these are represented by English and Ukrainian languages.The corpus of texts which were analyzed in our research has been taken from English scientific papers published in online scientific journals [11], [13], [15] from various academic fields, such as artificial intelligence, computer science, mathematics, chemistry, biology etc.The motivation to choose scientific discourse lies within the fact that academic language is rich in terminology, formality and special structures that allow to investigate the performance of GPT in different areas.After the analysis of a model was conducted, the outputs of ChatGPT were compared to the human translation and further investigated.Our investigation has shown that such a linguistic model is a powerful tool than can be used in the area of machine translation.Its structure and architecture contribute a lot to the identification of various patterns in text, which imitates the Věda a perspektivy № 11(42)2024