论文标题
顺序机器翻译的经验准确性法律：Google翻译的情况
An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate
论文作者
论文摘要
在这项研究中，我们通过经验测试建立了一项将翻译啤酒花数量与Google Translate连续机器翻译中的翻译精度相关的法律。准确性和大小随啤酒花次数而降低；遵循权力法，前者显示了密切的减少。这样的法律允许人们预测可能建立的翻译链的行为，因为社会越来越依赖自动化设备。
In this research, we have established, through empirical testing, a law that relates the number of translating hops to translation accuracy in sequential machine translation in Google Translate. Both accuracy and size decrease with the number of hops; the former displays a decrease closely following a power law. Such a law allows one to predict the behavior of translation chains that may be built as society increasingly depends on automated devices.
