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 larg...
| Autor: | |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:305519 |
| Acceso en línea: | https://ddd.uab.cat/record/305519 https://dx.doi.org/urn:doi:10.5565/rev/tradumatica.313 |
| Access Level: | acceso abierto |
| Palabra clave: | Preparació de corpus bilingüe Memòria de traducció Traducció automàtica Corpus trencard Bilingual corpus preparation Translation memory Machine translation Trencard corpus Preparación bilingüe de corpus Memoria de traduccion Traduccion automatica |
| Sumario: | 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. |
|---|