Tetiana Korolova
Doctor of Philology, Professor, Head of the Department of Translation, Theoretical and Applied Linguistics, State Institution “South Ukrainian National Pedagogical University named after K. D. Ushynsky”
Odesa, Ukraine
e-mail: kortami863@gmail.com
ORCID ID https://orcid.org/0000–0003–3441–196X
Natalya Zhmayeva
Ph.D. in Philology, Associate Professor at the Department of Translation and Theoretical and Applied Linguistics, State Institution «South Ukrainian National Pedagogical University named after K. D. Ushynsky»
Odesa, Ukraine
e-mail: zhmaeva@gmail.com
ORCID ID https://orcid.org/0000–0003–3382–0155
Yulia Kolchah
Master of Arts in Philology, State Institution «South Ukrainian National Pedagogical University named after K. D. Ushynsky»
Odesa, Ukraine
e-mail: juliaigorivna@ukr.net
DOI: https://doi.org/10.24195/2616-5317-2020-30-7
Key words: machine translation, informative text, Google Neural Machine Translation, translation quality level, type of post-editing.
Modern industry of translation services singles out two translation quality levels that can be reached as a result of machine translation (MT) post-editing: good enough quality foresees rendering the main information of the source message, admitting stylistic, syntactic and morphological flaws while quality similar or equal to human translation is a full dress version of a post-edited text, ready to be published.
The overview of MT systems enables us to consider Google Neural Machine Translation (GNMT) which is based on the most modern methods of training to reach maximum improvements the most powerful one.
When analyzing texts translated by means of Google Translate the following problems were identified: distortion of the referential meaning of the source message, incorrect choice of variant equivalences, lack of terms harmonization, lack of abbreviations rendering, inconformity of linguistic units in persons, numbers and cases, incorrect choice of functional correspondings when rendering absolute constructions, gerund and participial constructions, literal translation of phrases, lack of transformations of the grammatical structure of the source message (additions, rearrangements).
Taking into account the classified issues of machine translation as well as the levels of post-editing quality post-editing of the texts translated by means of MT is carried out, demands and recommendations applicable to post-editing results of MT within the language pair under analysis with respect to peculiarities of the specific MT system and the type of translated texts are provided.
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