QuEst for High Quality Machine Translation
نویسندگان
چکیده
منابع مشابه
QuEst for High Quality Machine Translation
In this paper we describe the use of QE, a framework that aims to obtain predictions on the quality of translations, to improve the performance of machine translation (MT) systems without changing their internal functioning. We apply QE to experiments with: i. multiple system translation ranking, where translations produced by different MT systems are ranked according to their estimated q...
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In this paper we present QE, an open source framework for machine translation quality estimation. The framework includes a feature extraction component and a machine learning component. We describe the architecture of the system and its use, focusing on the feature extraction component and on how to add new feature extractors. We also include experiments with features and learning algorithms...
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We describe QUEST, an open source framework for machine translation quality estimation. The framework allows the extraction of several quality indicators from source segments, their translations, external resources (corpora, language models, topic models, etc.), as well as language tools (parsers, part-of-speech tags, etc.). It also provides machine learning algorithms to build quality estimati...
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ژورنال
عنوان ژورنال: The Prague Bulletin of Mathematical Linguistics
سال: 2015
ISSN: 1804-0462
DOI: 10.1515/pralin-2015-0003