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Cross-Lingual Vector Representation of Language Units in the Task of Machine Translation

ФИО студента: Diana Gainutdinova

Руководитель: Oleg Durandin

Кампус/факультет: Faculty of Humanities (Nizhny Novgorod)

Программа: Fundamental and Applied Linguistics (Bachelor)

Год защиты: 2020

This research is devoted to the construction of a machine translation model that uses different types of cross-lingual and contextualized vector representation of words. The paper considered the linguistic bases of natural language processing (the concept of model, distributive semantics, compositionality), and also provided a comparative analysis of the basics of grammars of the Russian and Tatar languages (since the translation model was built for this pair). In the course of the work, a translation model was built based on the method of searching for nearest neighbors in a cross-language vector space. The resulting translation examples were analyzed from a linguistic point of view. The main characteristics of the sentence that are potentially important for the translation algorithm were highlighted.

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