论文标题
变压器时代的小说的机器翻译
Machine Translation of Novels in the Age of Transformer
论文作者
论文摘要
在本章中，我们建立了一个针对文学领域的机器翻译（MT）系统，特别是针对小说，基于Neural MT（NMT）的最新建筑，变压器（Vaswani等人，2017年），用于翻译方向英语，英语。随后，我们通过将该MT系统与其他三个系统（基于复发和短语范式下的两个域特异性系统和一个流行的通用在线系统）进行比较，通过评估其翻译来评估这种系统在多大程度上有用。第一个评估是自动的，并使用最宽敞的自动评估度量标准BLEU。剩下的两个评估是手动的，他们分别评估了使翻译无错误所需的偏好和后编辑量。正如预期的那样，在所有执行的三种评估中，基于域的特定变压器系统在所有情况下都优于其他三个系统。
In this chapter we build a machine translation (MT) system tailored to the literary domain, specifically to novels, based on the state-of-the-art architecture in neural MT (NMT), the Transformer (Vaswani et al., 2017), for the translation direction English-to-Catalan. Subsequently, we assess to what extent such a system can be useful by evaluating its translations, by comparing this MT system against three other systems (two domain-specific systems under the recurrent and phrase-based paradigms and a popular generic on-line system) on three evaluations. The first evaluation is automatic and uses the most-widely used automatic evaluation metric, BLEU. The two remaining evaluations are manual and they assess, respectively, preference and amount of post-editing required to make the translation error-free. As expected, the domain-specific Transformer-based system outperformed the three other systems in all the three evaluations conducted, in all cases by a large margin.
