期刊名称：The Prague Bulletin of Mathematical Linguistics
印刷版ISSN：0032-6585
电子版ISSN：1804-0462
出版年度：2009
卷号：91
期号：1
页码：47-56
DOI：10.2478/v10108-009-0015-5
语种：English
出版社：Walter de Gruyter GmbH
摘要：We describe a scalable decoder for parsing-based machine translation. The decoder is written in Java and implements all the essential algorithms described in (Chiang, 2007) and (Li and Khudanpur, 2008b): chart-parsing, n-gram language model integration, beam- and cube-pruning, and k-best extraction. Additionally, parallel and distributed computing techniques are exploited to make it scalable. We demonstrate experimentally that our decoder is more than 30 times faster than a baseline decoder written in Python.
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