This paper describes Charles University submission for Terminology translation Shared Task at WMT21. The objective of this task is to design a system which translates certain terms based on a provided terminology database, while preserving high overall translation quality. We competed in English-French language pair. Our approach is based on providing the desired translations alongside the input sentence and training the model to use these provided terms. We lemmatize the terms both during the training and inference, to allow the model to learn how to produce correct surface forms of the words, when they differ from the forms provided in the terminology database. Our submission ranked second in Exact Match metric which evaluates the ability of the model to produce desired terms in the translation.
翻译:本文件介绍查尔斯大学在WMT21提交的术语翻译共同任务报告,其目的是设计一个系统,根据所提供的术语数据库翻译某些术语,同时保持高总体翻译质量。我们以英法文对口进行竞争。我们的方法是在投入句的同时提供所需的翻译,并培训使用这些提供术语的模式。我们在培训和推论期间对术语进行区分,以便模型在与术语数据库提供的表格不同时,学习如何制作正确的词表表格式。我们的提交材料在评估模型在翻译中产生理想术语的能力的Exact Match 标准中名列第二。