论文标题
评估从法语到Bambara的人类翻译进行机器学习：试点研究
Assessing Human Translations from French to Bambara for Machine Learning: a Pilot Study
论文作者
论文摘要
我们提出了用于评估人类翻译的对齐文本的质量的新颖方法，用于学习资源不足的语言的机器翻译模型。马里大学的学生翻译了法语文本，将书面或口头翻译成班巴拉。我们的结果表明，可以从某些文本的书面翻译或口头翻译中获得类似的质量。他们还建议提供特定的说明，以提高其工作质量，以提高人类翻译。
We present novel methods for assessing the quality of human-translated aligned texts for learning machine translation models of under-resourced languages. Malian university students translated French texts, producing either written or oral translations to Bambara. Our results suggest that similar quality can be obtained from either written or spoken translations for certain kinds of texts. They also suggest specific instructions that human translators should be given in order to improve the quality of their work.
