Evaluation of translations into Plain German produced by humans and MT systems including ChatGPT

In this paper, we present the results of a study evaluating intralingual machine translations of health information texts into Plain German. In our study, we compare machine-translated simplified texts with those simplified manually by human translators, as well as with the original, unsimplified texts. We compare the output of four different machine translations systems and assess the translation quality using various criteria, including translation errors, readability, and syntactic complexity. The study reveals that from the four analysed machine translation systems, ChatGPT performed worst. Our results also suggest that fine-tuning a model with task-specific and domain-specific data improves the translation quality.

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Publication Details

Journal
SKASE Journal of translation and interpretation.
Published
2025-01-01
DOI
https://doi.org/10.33542/jti2025-s-3
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

Evaluation of translations into Plain German produced by humans and MT systems including ChatGPT

Ekaterina Lapshinova‐Koltunski, Silvana Deilen, Sarah Ahrens, Sergio Hernández Garrido
SKASE Journal of translation and interpretation.
Topic Modeling
article

Evaluation of translations into Plain German produced by humans and MT systems including ChatGPT

Ekaterina Lapshinova‐Koltunski, Silvana Deilen, Sarah Ahrens, Sergio Hernández Garrido
article en

Abstract

In this paper, we present the results of a study evaluating intralingual machine translations of health information texts into Plain German. In our study, we compare machine-translated simplified texts with those simplified manually by human translators, as well as with the original, unsimplified texts. We compare the output of four different machine translations systems and assess the translation quality using various criteria, including translation errors, readability, and syntactic complexity. The study reveals that from the four analysed machine translation systems, ChatGPT performed worst. Our results also suggest that fine-tuning a model with task-specific and domain-specific data improves the translation quality.

SKASE Journal of translation and interpretation.Vol. 18(2)
University of Hildesheim (DE)
Openalex Percentile: Top 86%
Topic Modeling
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