Combining Machine Translation Output with Open Source: The Carnegie Mellon Multi-Engine Machine Translation Scheme
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چکیده
منابع مشابه
Combining Machine Translation Output with Open SourceThe Carnegie Mellon Multi-Engine Machine Translation Scheme
The Carnegie Mellon multi-engine machine translation software merges output from several machine translation systems into a single improved translation. This improvement is significant: in the recent NIST MT09 evaluation, the combined Arabic-English output scored 5.22 BLEU points higher than the best individual system. Concurrent with this paper, we release the source code behind this result co...
متن کاملCombining Machine Translation Output with Open Source
The Carnegie Mellon multi-engine machine translation software merges output from several machine translation systems into a single improved translation. This improvement is significant: in the recent NIST MT09 evaluation, the combined Arabic-English output scored 5.22 BLEU points higher than the best individual system. Concurrent with this paper, we release the source code behind this result co...
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We describe an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source dec...
متن کاملMulti-Engine Machine Translation with an Open-Source SMT Decoder
We describe an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source dec...
متن کاملCombining Resources for Open Source Machine Translation
In this paper, we present a Japanese→English machine translation system that combines rule-based and statistical translation. Our system is unique in that all of its components are freely available as open source software. We describe the development of the rule-based translation engine including transfer rule acquisition from an open bilingual dictionary. We also show how translations from bot...
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ژورنال
عنوان ژورنال: The Prague Bulletin of Mathematical Linguistics
سال: 2010
ISSN: 1804-0462,0032-6585
DOI: 10.2478/v10108-010-0008-4