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Online optimisation of log-linear weights in interactive machine translation

机译:交互式机器翻译中对数线性权重的在线优化

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Whenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a setup, it is crucial that the system is able to learn from the errors that have already been corrected. In this paper, we analyse the applicability of discriminative ridge regression for learning the log-linear weights of a state-of-the-art machine translation system underlying an interactive machine translation framework, with encouraging results.
机译:只要机器翻译系统提供的质量不够高,就需要由专家来纠正机器翻译系统提供的句子。在这样的设置中,至关重要的是系统能够从已经纠正的错误中学习。在本文中,我们分析了判别岭回归在学习基于交互式机器翻译框架的最新机器翻译系统的对数线性权重方面的适用性,并获得了令人鼓舞的结果。

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