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Statistical machine translation of patents requires large amounts of sentence-parallel data. Translations of patent text often exist for parts of the patent document, namely title, abstract and claims. However , there are no direct translations of the largest part of the document, the description or background of the invention. We document a twofold(More)
We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on features extracted with statistical machine translation methods and tools, combining mono-lingual and cross-lingual word alignments as well as standard textual entailment distance and bag-of-words features in a statistical(More)
Patent translation is a complex problem due to the highly specialized technical vocabulary and the peculiar textual structure of patent documents. In this paper we analyze patents along the orthogonal dimensions of topic and textual structure. We view different patent classes and different patent text sections such as title, abstract, and claims, as(More)
Recent research has shown that accuracy and speed of human translators can benefit from post-editing output of machine translation systems, with larger benefits for higher quality output. We present an efficient online learning framework for adapting all modules of a phrase-based statistical machine translation system to post-edited translations. We use a(More)
We present experiments on multi-task learning for discriminative training in statistical machine translation (SMT), extending standard minimum-error-rate training (MERT) by techniques that take advantage of the similarity of related tasks. We apply our techniques to German-to-English translation of patents from 8 tasks according to the International Patent(More)
Translation memories (TM) are widely used in the localization industry to improve consistency and speed of human translation. Several approaches have been presented to integrate the bilingual translation units of TMs into statistical machine translation (SMT). We present an extension of these approaches to the integration of partial matches found in a(More)
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