This paper presents the submission of the Arni Magnusson Institute’s team to the WMT24 General translation task. We work on the English→Icelandic translation direction. Our system comprises four translation models and a grammar correction model. For training our systems we carefully curate our datasets, aggressively filtering out sentence pairs that may detrimentally affect the quality of our systems output. Some of our data are collected from human translations and some are synthetically generated. A part of the synthetic data is generated using an LLM, and we find that it increases the translation capability of our system significantly.

The submission of the Árni Magnússon Institute’s team to the WMT24 test suite subtask focuses on idiomatic expressions and proper names for the English→Icelandic translation direction. Intuitively and empirically, idioms and proper names are known to be a significant challenge for neural translation models. We create two different test suites. The first evaluates the competency of MT systems in translating common English idiomatic expressions, as well as testing whether systems can distinguish between those expressions and the same phrases when used in a literal context. The second test suite consists of place names that should be translated into their Icelandic exonyms (and correctly inflected) and pairs of Icelandic names that share a surface form between the male and female variants, so that incorrect translations impact meaning as well as readibility. The scores reported are relatively low, especially for idiomatic expressions and place names, and indicate considerable room for improvement.