团队构建四模型系统，提升英译冰岛语质量。
Cogs in a Machine, Doing What They're Meant to Do -- The AMI Submission to the WMT24 General Translation Task
- 四翻译模型+语法修正模型，数据经严格筛选。
- 合成数据（含LLM生成）显著提升翻译能力。
- 适合关注低资源语言翻译的学者与工程师。
本文介绍阿恩尼·马格努松研究所团队参加WMT24通用翻译任务的提交方案。研究聚焦英语到冰岛语的翻译方向。系统由四个翻译模型和一个语法纠错模型构成。训练数据经过精心筛选，主动剔除可能降低输出质量的句子对。部分数据来自人工翻译，部分为合成生成。其中一部分合成数据使用大语言模型生成，实验表明该方法显著提升了系统的翻译能力。
原文摘要 · Abstract (English)
This paper presents the submission of the Árni 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 models we carefully curate our datasets, aggressively filtering out sentence pairs that may detrimentally affect the quality of our system's 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.
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