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arxiv: 1805.07469 · v1 · pith:7NVVUVY3new · submitted 2018-05-18 · 💻 cs.CL

Metric for Automatic Machine Translation Evaluation based on Universal Sentence Representations

classification 💻 cs.CL
keywords sentencerepresentationstranslationevaluationmachineautomaticfeaturesuniversal
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Sentence representations can capture a wide range of information that cannot be captured by local features based on character or word N-grams. This paper examines the usefulness of universal sentence representations for evaluating the quality of machine translation. Although it is difficult to train sentence representations using small-scale translation datasets with manual evaluation, sentence representations trained from large-scale data in other tasks can improve the automatic evaluation of machine translation. Experimental results of the WMT-2016 dataset show that the proposed method achieves state-of-the-art performance with sentence representation features only.

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