利用GPT-4进行自动翻译后编辑

Leveraging GPT-4 for Automatic Translation Post-Editing

May 24, 2023

作者: Vikas Raunak, Amr Sharaf, Hany Hassan Awadallah, Arul Menezes

cs.AI

摘要

尽管神经机器翻译（NMT）代表着机器翻译（MT）的主导方法，但NMT模型的输出仍需要翻译后编辑以纠正错误并提高质量，尤其是在关键环境下。在这项工作中，我们将使用大型语言模型（LLMs）正式规范翻译后编辑任务，并探索使用GPT-4自动对多种语言对的NMT输出进行后编辑。我们的结果表明，GPT-4擅长翻译后编辑，并且即使目标语言不是英语，也能产生有意义的编辑。值得注意的是，我们利用基于GPT-4的后编辑，在WMT-22英中、英德、中英和德英语言对上实现了最先进的性能，经过最先进的MT质量指标评估。

English

While Neural Machine Translation (NMT) represents the leading approach to Machine Translation (MT), the outputs of NMT models still require translation post-editing to rectify errors and enhance quality, particularly under critical settings. In this work, we formalize the task of translation post-editing with Large Language Models (LLMs) and explore the use of GPT-4 to automatically post-edit NMT outputs across several language pairs. Our results demonstrate that GPT-4 is adept at translation post-editing and produces meaningful edits even when the target language is not English. Notably, we achieve state-of-the-art performance on WMT-22 English-Chinese, English-German, Chinese-English and German-English language pairs using GPT-4 based post-editing, as evaluated by state-of-the-art MT quality metrics.