Investigating backtranslation for the improvement of English-Irish machine translation

Q2 Arts and Humanities
Teanga Pub Date : 2019-11-29 DOI:10.35903/teanga.v26i0.88
Meghan Dowling, Teresa Lynn
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引用次数: 2

Abstract

In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.
探讨反译对英-爱尔兰语机器翻译的改进
本文讨论了为英语-爱尔兰语(EN-GA)语言对建立可靠的机器翻译系统的困难。在有限数据集的背景下,我们报告了评估反向翻译作为创建人工EN-GA数据的方法的使用,以增加使用最先进的数据驱动翻译系统的训练数据。我们将我们的结果与Dowling等人(2016、2017、2018)在EN-GA机器翻译方面的早期工作进行了比较,结果表明,虽然我们自己的系统在质量上无法与传统报告的BLEU指标进行比较,但我们提供了一项语言分析,表明未来针对特定领域数据的工作可能会更成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Teanga
Teanga Arts and Humanities-Language and Linguistics
CiteScore
0.70
自引率
0.00%
发文量
13
审稿时长
26 weeks
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