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RTM results for Predicting Translation Performance

机译:RTM结果可预测翻译效果

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摘要

With improved prediction combination using weights based on their training performance and stacking and multilayer perceptrons to build deeper prediction models, RTMs become the 3rd system in general at the sentence-level prediction of translation scores and achieve the lowest RMSE in English to German NMT QET results. For the document-level task, we compare document-level RTM models with sentence-level RTM models obtained with the concatenation of document sentences and obtain similar results.
机译:通过使用基于权重的训练性能和堆叠以及多层感知器改进的预测组合来构建更深的预测模型,RTM在句子翻译水平的句子级别预测中通常成为第三种系统,并且英语到德语的NMT QET结果达到最低的RMSE 。对于文档级任务,我们将文档级RTM模型与通过文档句子串联而获得的句子级RTM模型进行比较,并获得相似的结果。

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