文章基本信息

标题：Hybrid Machine Translation by Combining Output from Multiple Machine Translation Systems
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作者：Matīss Rikters
期刊名称：Baltic Journal of Modern Computing
印刷版ISSN：2255-8942
电子版ISSN：2255-8950
出版年度：2019
卷号：7
期号：3
页码：1-41
DOI：10.22364/bjmc.2019.7.3.01
出版社：Vilnius University, University of Latvia, Latvia University of Agriculture, Institute of Mathematics and Informatics of University of Latvia
摘要：This paper aims to combine output from various machine translation (MT) systems so that the overall translation quality of the source text would increase. Applicability of the developed methods for small, morphologically rich and under-resourced languages is evaluated, especially Latvian and Estonian. Existing methods have been analysed, and several combinations of methods have been proposed. The proposed methods have been implemented and evaluated using automatic and human evaluation. During this research novel methods have been created that structure source language sentences into linguistically motivated fragments and combine them using a character level neural language model; combine neural machine translation output by employing sourcetranslation attention alignments; use a multi-pass approach to produce additional incrementally improving training data. The key results of this research are new state-of-the-art machine translation systems for English ↔ Estonian; approaches for utilising neural MT generated attention alignments for MT combination and comprehension of resulting translations; MT combination systems for combining output from English → Latvian statistical MT. A practical application of the methods is implemented and described.
关键词：Machine Translation; Hybrid Machine Translation; Machine Translation System Combination; Multi;System Machine Translation