TY - JOUR AU - Dowling, Meghan AU - Lynn, Teresa AU - Way, Andy PY - 2019/11/29 Y2 - 2024/03/28 TI - Investigating backtranslation for the improvement of English-Irish machine translation JF - TEANGA, the Journal of the Irish Association for Applied Linguistics JA - TEANGA VL - 26 IS - SE - Articles DO - 10.35903/teanga.v26i0.88 UR - https://journal.iraal.ie/index.php/teanga/article/view/88 SP - 1–25 AB - <p><span style="font-weight: 400;">In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.</span></p> ER -