An Analysis of Source-Side Grammatical Errors in NMT
An Analysis of Source-Side Grammatical Errors in NMT
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DOI：
10.18653/v1/w19-4822
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发表时间：
2019-05
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影响因子：
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通讯作者：
Antonios Anastasopoulos
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文献类型：
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作者：
Antonios Anastasopoulos
神经机器翻译（NMT）的质量在面对源端噪声时会显着下降。本文通过对几个语法校正语料库的评估，首次对最先进的英语到德语的NMT中的真实的语法噪音进行了大规模的研究。我们提出的方法来评估NMT的鲁棒性没有真正的参考，我们用它们进行广泛的分析，不同的语法错误对NMT输出的影响。我们还介绍了一种技术，用于可视化由源端错误引起的发散分布，这允许额外的见解。
The quality of Neural Machine Translation (NMT) has been shown to significantly degrade when confronted with source-side noise. We present the first large-scale study of state-of-the-art English-to-German NMT on real grammatical noise, by evaluating on several Grammar Correction corpora. We present methods for evaluating NMT robustness without true references, and we use them for extensive analysis of the effects that different grammatical errors have on the NMT output. We also introduce a technique for visualizing the divergence distribution caused by a source-side error, which allows for additional insights.