Search Results for author: Maria Kunilovskaya

Found 5 papers, 0 papers with code

Lexicogrammatic translationese across two targets and competence levels

no code implementations LREC 2020 Maria Kunilovskaya, Ekaterina Lapshinova-Koltunski

This research employs genre-comparable data from a number of parallel and comparable corpora to explore the specificity of translations from English into German and Russian produced by students and professional translators.

Towards Functionally Similar Corpus Resources for Translation

no code implementations RANLP 2019 Maria Kunilovskaya, Serge Sharoff

We exploit a text-external approach, based on a set of Functional Text Dimensions to model text functions, so that each text can be represented as a vector in a multidimensional space of text functions.

Translationese Features as Indicators of Quality in English-Russian Human Translation

no code implementations RANLP 2019 Maria Kunilovskaya, Ekaterina Lapshinova-Koltunski

We use a range of morpho-syntactic features inspired by research in register studies (e. g. Biber, 1995; Neumann, 2013) and translation studies (e. g. Ilisei et al., 2010; Zanettin, 2013; Kunilovskaya and Kutuzov, 2018) to reveal the association between translationese and human translation quality.

Size vs. Structure in Training Corpora for Word Embedding Models: Araneum Russicum Maximum and Russian National Corpus

no code implementations19 Jan 2018 Andrey Kutuzov, Maria Kunilovskaya

Aside from the already known fact that the RNC is generally a better training corpus than web corpora, we enumerate and explain fine differences in how the models process semantic similarity task, what parts of the evaluation set are difficult for particular models and why.

Semantic Similarity Semantic Textual Similarity

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