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Enhancing Scientific Discourse: Machine Translation for the Scientific Domain

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Computer Science > Computation and Language

arXiv:2605.20912 (cs)
[Submitted on 20 May 2026]

Title:Enhancing Scientific Discourse: Machine Translation for the Scientific Domain

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Abstract:The increasing volume of scientific research necessitates effective communication across language barriers. Machine translation (MT) offers a promising solution for accessing international publications. However, the scientific domain presents unique challenges due to its specialized vocabulary and complex sentence structures. In this paper, we present the development of a collection of parallel and monolingual corpora for the scientific domain. The corpora target the language pairs Spanish-English, French-English, and Portuguese-English. For each language pair, we create a large general scientific corpus as well as four smaller corpora focused on the domains of: Cancer Research, Energy Research, Neuroscience, and Transportation research. To evaluate the quality of these corpora, we utilize them for fine-tuning general-purpose neural machine translation (NMT) systems. We provide details regarding the corpus creation process, the fine-tuning strategies employed, and we conclude with the evaluation results.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2605.20912 [cs.CL]
  (or arXiv:2605.20912v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.20912
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Sokratis Sofianopoulos [view email]
[v1] Wed, 20 May 2026 08:57:41 UTC (27 KB)
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