Creating Domain-Specific Translation Memories for Machine Translation Fine-Tuning

This article investigates how translation memories (TMs) can be created by translators or other language professionals in order to compile domain-specific parallel corpora, which can then be used in different scenarios, such as machine translation training and fine-tuning, TM leveraging, and/or large language model fine-tuning. The article introduces a semi-automatic TM preparation methodology that primarily leverages translation tools used by translators, in the interests of data quality and control by translators themselves. This semi-automatic methodology is then used to build a cardiology-based Turkish → English corpus from bilingual abstracts of Turkish cardiology journals. The resulting corpus, called TRENCARD Corpus, has approximately 800,000 source words and 50,000 sentences. Using this methodology, translators can build custom TMs in a reasonable time and use them in tasks requiring bilingual data.