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检索条件"任意字段=Proceedings of the Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation"
56 条 记 录,以下是41-50 订阅
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A general-purpose rule extractor for SCFG-based machine translation  5
A general-purpose rule extractor for SCFG-based machine tran...
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5th workshop on syntax, semantics and structure in statistical translation, SSST 2011 at the Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL HLT 2011
作者: Hanneman, Greg Burroughs, Michelle Lavie, Alon Language Technologies Institute Carnegie Mellon University PittsburghPA15213 United States
We present a rule extractor for SCFG-based MT that generalizes many of the contraints present in existing SCFG extraction algorithms. Our method’s increased rule coverage comes from allowing multiple alignments, virt... 详细信息
来源: 评论
structured vs. Flat semantic role representations for machine translation evaluation  5
Structured vs. Flat semantic role representations for machin...
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5th workshop on syntax, semantics and structure in statistical translation, SSST 2011 at the Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL HLT 2011
作者: Lo, Chi-Kiu Wu, Dekai HKUST Human Language Technology Center Dept. of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong
We argue that failing to capture the degree of contribution of each semantic frame in a sentence explains puzzling results in recent work on the MEANT family of semantic MT evaluation metrics, which have disturbingly ... 详细信息
来源: 评论
Improving reordering for statistical machine translation with smoothed priors and syntactic features  5
Improving reordering for statistical machine translation wit...
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Bing Xiang Niyu Ge Abraham Ittycheriah IBM T. J. Watson Research Center Yorktown Heights NY
In this paper we propose several novel approaches to improve phrase reordering for statistical machine translation in the framework of maximum-entropy-based modeling. A smoothed prior probability is introduced to take...
来源: 评论
Combining statistical and semantic approaches to the translation of ontologies and taxonomies  5
Combining statistical and semantic approaches to the transla...
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: John McCrae Mauricio Espinoza Elena Montiel-Ponsoda Guadalupe Aguado-de-Cea Philipp Cimiano Universität Bielefeld Bielefeld Germany Universidad de Cuenca Cuenca Ecuador Universidad Politécnica de Madrid Madrid Spain
Ontologies and taxonomies are widely used to organize concepts providing the basis for activities such as indexing, and as background knowledge for NLP tasks. As such, translation of these resources would prove useful...
来源: 评论
A dependency based statistical translation model  5
A dependency based statistical translation model
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Giuseppe Attardi Atanas Chanev Antonio Valerio Miceli Barone Universitá di Pisa
We present a translation model based on dependency trees. The model adopts a tree-to-string approach and extends Phrase-Based translation (PBT) by using the dependency tree of the source sentence for selecting transla...
来源: 评论
Automatic category label coarsening for syntax-based machine translation  5
Automatic category label coarsening for syntax-based machine...
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Greg Hanneman Alon Lavie Carnegie Mellon University Pittsburgh PA
We consider SCFG-based MT systems that get syntactic category labels from parsing both the source and target sides of parallel training data. The resulting joint nonterminals often lead to needlessly large label sets ...
来源: 评论
Automatic projection of semantic structures: an application to pairwise translation ranking  5
Automatic projection of semantic structures: an application ...
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Daniele Pighin Lluís Màrquez Universitat Politècnica de Catalunya
We present a model for the inclusion of semantic role annotations in the framework of confidence estimation for machine translation. The model has several interesting properties, most notably: 1) it only requires a li...
来源: 评论
A general-purpose rule extractor for SCFG-based machine translation  5
A general-purpose rule extractor for SCFG-based machine tran...
收藏 引用
proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Greg Hanneman Michelle Burroughs Alon Lavie Carnegie Mellon University Pittsburgh PA
We present a rule extractor for SCFG-based MT that generalizes many of the contraints present in existing SCFG extraction algorithms. Our method's increased rule coverage comes from allowing multiple alignments, v...
来源: 评论
A semantic feature for statistical machine translation  5
A semantic feature for statistical machine translation
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Rafael E. Banchs Marta R. Costa-jussà Institute for Infocomm Research Singapore Barcelona Media Innovation Centre planta Barcelona
A semantic feature for statistical machine translation, based on Latent Semantic Indexing, is proposed and evaluated. The objective of the proposed feature is to account for the degree of similarity between a given in...
来源: 评论
Multi-word unit dependency forest-based translation rule extraction  5
Multi-word unit dependency forest-based translation rule ext...
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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation
作者: Hwidong Na Jong-Hyeok Lee Pohang University of Science and Technology (POSTECH) Pohang Republic of Korea
translation requires non-isomorphic transformation from the source to the target. However, non-isomorphism can be reduced by learning multi-word units (MWUs). We present a novel way of representating sentence structur...
来源: 评论