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Machine vs. Human: Exploring Syntax and Lexicon in German Translations, with a Spotlight on Anglicisms


Shaitarova, Anastassia; Göhring, Anne; Volk, Martin (2023). Machine vs. Human: Exploring Syntax and Lexicon in German Translations, with a Spotlight on Anglicisms. In: The 24th Nordic Conference on Computational Linguistics (NoDaLiDa), Tórshavn, Faroe Islands, 23 May 2023 - 25 May 2023. University of Tartu Library, 215-227.

Abstract

Machine Translation (MT) has become an integral part of daily life for millions of people, with its output being so fluent that users often cannot distinguish it from human translation. However, these fluid texts often harbor algorithmic traces, from limited lexical choices to societal misrepresentations. This raises concerns about the possible effects of MT on natural language and human communication and calls for regular evaluations of machine-generated translations for different languages. Our paper explores the output of three widely used engines (Google, DeepL, Microsoft Azure) and one smaller commercial system. We translate the English and French source texts of seven diverse parallel corpora into German and compare MT-produced texts to human references in terms of lexical, syntactic, and morphological features. Additionally, we investigate how MT leverages lexical borrowings and analyse the distribution of anglicisms across the German translations.

Abstract

Machine Translation (MT) has become an integral part of daily life for millions of people, with its output being so fluent that users often cannot distinguish it from human translation. However, these fluid texts often harbor algorithmic traces, from limited lexical choices to societal misrepresentations. This raises concerns about the possible effects of MT on natural language and human communication and calls for regular evaluations of machine-generated translations for different languages. Our paper explores the output of three widely used engines (Google, DeepL, Microsoft Azure) and one smaller commercial system. We translate the English and French source texts of seven diverse parallel corpora into German and compare MT-produced texts to human references in terms of lexical, syntactic, and morphological features. Additionally, we investigate how MT leverages lexical borrowings and analyse the distribution of anglicisms across the German translations.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:25 May 2023
Deposited On:16 Jun 2023 10:08
Last Modified:03 Jan 2024 14:01
Publisher:University of Tartu Library
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://aclanthology.org/2023.nodalida-1.22
Project Information:
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)