论文标题
SCB-MT-en-th-2020：一个大的英语 - 泰语平行语料库
scb-mt-en-th-2020: A Large English-Thai Parallel Corpus
论文作者
论文摘要
我们工作的主要目的是构建用于机器翻译的大规模英语thai数据集。我们构建了一个具有超过100万个段的英语Thai Machine Translation数据集，该数据集由各种来源策划，即新闻，Wikipedia文章，SMS消息，基于任务的对话框，网上拖网数据和政府文档。收集数据，构建平行文本和删除嘈杂句子对的方法以可重复的方式提出。我们基于此数据集训练机器翻译模型。当开放的平行语料库（OPUS）包含在泰语 - 英语和英语 - 泰语翻译的培训数据中，我们的模型的性能与泰语 - 英语和跑赢大盘的Google Translation API（截至2020年5月）相当。可以公开使用的数据集，预训练的模型和源代码来重现我们的工作。
The primary objective of our work is to build a large-scale English-Thai dataset for machine translation. We construct an English-Thai machine translation dataset with over 1 million segment pairs, curated from various sources, namely news, Wikipedia articles, SMS messages, task-based dialogs, web-crawled data and government documents. Methodology for gathering data, building parallel texts and removing noisy sentence pairs are presented in a reproducible manner. We train machine translation models based on this dataset. Our models' performance are comparable to that of Google Translation API (as of May 2020) for Thai-English and outperform Google when the Open Parallel Corpus (OPUS) is included in the training data for both Thai-English and English-Thai translation. The dataset, pre-trained models, and source code to reproduce our work are available for public use.
