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检索条件"任意字段=Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation"
43 条 记 录,以下是31-40 订阅
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Chunk-level reordering of source language sentences with automatically learned rules for statistical machine translation
Chunk-level reordering of source language sentences with aut...
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2007 amta workshop on syntax and structure in statistical translation, SSST 2007 at the 2007 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, naacl-hlt 2007
作者: Zhang, Yuqi Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
In this paper, we describe a source-side reordering method based on syntactic chunks for phrase-based statistical machine translation. First, we shallow parse the source language sentences. Then, reordering rules are ... 详细信息
来源: 评论
Dependency-based automatic evaluation for machine translation
Dependency-based automatic evaluation for machine translatio...
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2007 amta workshop on syntax and structure in statistical translation, SSST 2007 at the 2007 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, naacl-hlt 2007
作者: Owczarzak, Karolina van Genabith, Josef Way, Andy National Centre for Language Technology School of Computing Dublin City University Dublin 9 Ireland
We present a novel method for evaluating the output of Machine translation (MT), based on comparing the dependency structures of the translation and reference rather than their surface string forms. Our method uses a ... 详细信息
来源: 评论
Generating case markers in machine translation
Generating case markers in machine translation
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Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, naacl hlt 2007
作者: Toutanova, Kristina Suzuki, Hisami Microsoft Research One Microsoft Way Redmond WA 98052 United States
We study the use of rich syntax-based statistical models for generating grammatical case for the purpose of machine translation from a language which does not indicate case explicitly (English) to a language with a ri... 详细信息
来源: 评论
Probabilistic synchronous tree-adjoining grammars for machine translation: the argument from bilingual dictionaries  07
Probabilistic synchronous tree-adjoining grammars for machin...
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Stuart M. Shieber Harvard University Cambridge MA
We provide a conceptual basis for thinking of machine translation in terms of synchronous grammars in general, and probabilistic synchronous tree-adjoining grammars in particular. Evidence for the view is found in the...
来源: 评论
A walk on the other side: adding statistical components to a transfer-based translation system  07
A walk on the other side: adding statistical components to a...
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Ariadna Font Llitjós Stephan Vogel Carnegie Mellon University Pittsburgh PA
This paper seeks to complement the current trend of adding more structure to statistical Machine translation systems, by exploring the opposite direction: adding statistical components to a Transfer-Based MT system. I...
来源: 评论
Machine translation as tree labeling  07
Machine translation as tree labeling
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Mark Hopkins Jonas Kuhn University of Potsdam Germany
We present the main ideas behind a new syntax-based machine translation system, based on reducing the machine translation task to a tree-labeling task. This tree labeling is further reduced to a sequence of decisions ...
来源: 评论
Extraction phenomena in synchronous TAG syntax and semantics  07
Extraction phenomena in synchronous TAG syntax and semantics
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Rebecca Nesson Stuart M. Shieber Harvard University Cambridge MA
We present a proposal for the structure of noun phrases in Synchronous Tree-Adjoining Grammar (STAG) syntax and semantics that permits an elegant and uniform analysis of a variety of phenomena, including quantifier sc...
来源: 评论
Chunk-level reordering of source language sentences with automatically learned rules for statistical machine translation  07
Chunk-level reordering of source language sentences with aut...
收藏 引用
proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Yuqi Zhang Richard Zens Hermann Ney RWTH Aachen University Aachen Germany
In this paper, we describe a source-side reordering method based on syntactic chunks for phrase-based statistical machine translation. First, we shallow parse the source language sentences. Then, reordering rules are ...
来源: 评论
Generation in machine translation from deep syntactic trees  07
Generation in machine translation from deep syntactic trees
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: Keith Hall Petr Němec Johns Hopkins University Baltimore MD Charles University Prague Czech Republic
In this paper we explore a generative model for recovering surface syntax and strings from deep-syntactic tree structures. Deep analysis has been proposed for a number of language and speech processing tasks, such as ...
来源: 评论
Combining morphosyntactic enriched representation with n-best reranking in statistical translation  07
Combining morphosyntactic enriched representation with n-bes...
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proceedings of the naacl-hlt 2007/amta workshop on syntax and structure in statistical translation
作者: H. Bonneau-Maynard A. Allauzen D. Déchelotte H. Schwenk LIMSI-CNRS Orsay cedex France
The purpose of this work is to explore the integration of morphosyntactic information into the translation model itself, by enriching words with their morphosyntactic categories. We investigate word disambiguation usi...
来源: 评论