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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"

共 56 条记录，以下是31-40 订阅

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CombiningWord Reordering Methods on different Linguistic Abstraction Levels for statistical Machine translation 7

CombiningWord Reordering Methods on different Linguistic Abs...

引用

7th workshop on syntax, semantics and structure in statistical translation, SSST 2013

作者： Herrmann, Teresa Niehues, Jan Waibel, Alex Institute for Anthropomatics Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9781937284473

We describe a novel approach to combining lexicalized, POS-based and syntactic treebased word reordering in a phrase-based machine translation system. Our results show that each of the presented reordering methods leads to improved translation quality on its own. The strengths however can be combined to achieve further improvements. We present experiments on German-English and German- French translation. We report improvements of 0.7 BLEU points by adding tree-based and lexicalized reordering. Up to 1.1 BLEU points can be gained by POS and tree-based reordering over a baseline with lexicalized reordering. A human analysis, comparing subjective translation quality as well as a detailed error analysis show the impact of our presented tree-based rules in terms of improved sentence quality and reduction of errors related to missing verbs and verb positions. ©2013 Association for Computational Linguistics.

关键词： Error analysis

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Head finalization reordering for Chinese-to-Japanese machine translation 6

Head finalization reordering for Chinese-to-Japanese machine...

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6th workshop on syntax, semantics and structure in statistical translation, SSST 2012 at the 50th Annual Meeting of the Association for Computational Linguistics, ACT 2012

作者： Dan, Han Sudoh, Katsuhito Wu, Xianchao Duh, Kevin Tsukada, Hajime Nagata, Masaaki The Graduate University For Advanced Studies Tokyo Japan NTT Communication Science Laboratories NTT Corporation Japan Baidu Japan Inc Japan Japan

ISBN: (纸本)9781937284381

In statistical Machine translation, reordering rules have proved useful in extracting bilingual phrases and in decoding during translation between languages that are structurally different. Linguistically motivated rules have been incorporated into Chinese-to-English (Wang et al., 2007) and English-to-Japanese (Isozaki et al., 2010b) translation with significant gains to the statistical translation system. Here, we carry out a linguistic analysis of the Chinese-to-Japanese translation problem and propose one of the first reordering rules for this language pair. Experimental results show substantially improvements (from 20.70 to 23.17 BLEU) when head-finalization rules based on HPSG parses are used, and further gains (to 24.14 BLEU) were obtained using more refined rules. © 2012 Association for Computational Linguistics.

关键词： Machine translation

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Synchronous Linear Context-Free Rewriting Systems for Machine translation 7

Synchronous Linear Context-Free Rewriting Systems for Machin...

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7th workshop on syntax, semantics and structure in statistical translation, SSST 2013

作者： Kaeshammer, Miriam University of D¨usseldorf Universiẗatsstraße 1 Düsseldorf40225 Germany

ISBN: (纸本)9781937284473

We propose synchronous linear context-free rewriting systems as an extension to synchronous context-free grammars in which synchronized non-terminals span k 1 continuous blocks on each side of the bitext. Such discontinuous constituents are required for inducing certain alignment configurations that occur relatively frequently in manually annotated parallel corpora and that cannot be generated with less expressive grammar formalisms. As part of our investigations concerning the minimal k that is required for inducing manual alignments, we present a hierarchical aligner in form of a deduction system. We find that by restricting k to 2 on both sides, 100% of the data can be covered. ©2013 Association for Computational Linguistics.

关键词： Context free grammars

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Automatic category label coarsening for syntax-based machine translation 5

Automatic category label coarsening for syntax-based machine...

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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 Lavie, Alon Language Technologies Institute Carnegie Mellon University PittsburghPA15213 United States

ISBN: (纸本)9781932432992

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 that are not optimized for an MT scenario. This paper presents a method of iteratively coarsening a label set for a particular language pair and training corpus. We apply this label collapsing on Chinese–English and French–English grammars, obtaining test-set improvements of up to 2.8 BLEU, 5.2 TER, and 0.9 METEOR on Chinese–English translation. An analysis of label collapsing’s effect on the grammar and the decoding process is also given. © 2011 Association for Computational Linguistics

关键词： Coarsening

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Automatic projection of semantic structures: An application to pairwise translation ranking 5

Automatic projection of semantic structures: An application ...

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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： Pighin, Daniele Màrquez, Lluís TALP Research Center Universitat Politècnica de Catalunya Spain

ISBN: (纸本)9781932432992

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 linguistic processor on the (generally well-formed) source side of the translation;2) it does not directly rely on properties of the translation model (hence, it can be applied beyond phrase-based systems). These features make it potentially appealing for system ranking, translation re-ranking and user feedback evaluation. Preliminary experiments in pairwise hypothesis ranking on five confidence estimation benchmarks show that the model has the potential to capture salient aspects of translation quality. © 2011 Association for Computational Linguistics

关键词： Benchmarking

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Improving statistical machine translation through co-joining parts of verbal constructs in English-Hindi translation 6

Improving statistical machine translation through co-joining...

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6th workshop on syntax, semantics and structure in statistical translation, SSST 2012 at the 50th Annual Meeting of the Association for Computational Linguistics, ACT 2012

作者： Arora, Karunesh Kumar Sinha, Mahesh K. CDAC Anusandhan Bhawan C 56/1 Sector 62 Noida India JSS Academy of Technical Education C 20/1 Sector 62 Noida India

ISBN: (纸本)9781937284381

Verb plays a crucial role of specifying the action or function performed in a sentence. In translating English to morphologically richer language like Hindi, the organization and the order of verbal constructs contributes to the fluency of the language. Mere statistical methods of machine translation are not sufficient enough to consider this aspect. Identification of verb parts in a sentence is essential for its understanding and they constitute as if they are a single entity. Considering them as a single entity improves the translation of the verbal construct and thus the overall quality of the translation. The paper describes a strategy for pre-processing and for identification of verb parts in source and target language corpora. The steps taken towards reducing sparsity further helped in improving the translation results. © 2012 Association for Computational Linguistics.

关键词： Machine translation

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Harmonizing word alignments and syntactic structures for extracting phrasal translation equivalents 9

Harmonizing word alignments and syntactic structures for ext...

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9th workshop on syntax, semantics and structure in statistical translation, SSST 2015 at the NAACL HLT 2015

作者： Deng, Dun Xue, Nianwen Guo, Shiman Computer Science Department Brandeis University 415 South Street WalthamMA02453 United States

ISBN: (纸本)9781941643419

Accurate identification of phrasal translation equivalents is critical to both phrase-based and syntax-based machine translation systems. We show that the extraction of many phrasal translation equivalents is made impossible by word alignments done without taking syntactic structures into consideration. To address the problem, we propose a new annotation scheme where word alignment and the alignment of non-terminal nodes (i.e., phrases) are done simultaneously to avoid conflicts between word alignments and syntactic structures. Relying on this new alignment approach, we construct a Hierarchically Aligned Chinese-English Parallel Treebank (HACEPT), and show that all phrasal translation equivalents can be automatically extracted based on the phrase alignments in HACEPT. © 2015 Association for Computational Linguistics

关键词： Alignment

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Decoding with syntactic and non-syntactic phrases in a syntax-based machine translation system 3

Decoding with syntactic and non-syntactic phrases in a synta...

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3rd workshop on syntax and structure in statistical translation, SSST 2009 at the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2009

作者： Hanneman, Greg Lavie, Alon Language Technologies Institute Carnegie Mellon University PittsburghPA15213 United States

ISBN: (纸本)9781932432398

A key concern in building syntax-based machine translation systems is how to improve coverage by incorporating more traditional phrase-based SMT phrase pairs that do not correspond to syntactic constituents. At the same time, it is desirable to include as much syntactic information in the system as possible in order to carry out linguistically motivated reordering, for example. We apply an extended and modified version of the approach of Tinsley et al. (2007), extracting syntax-based phrase pairs from a large parallel parsed corpus, combining them with PBSMT phrases, and performing joint decoding in a syntax-based MT framework without loss of translation quality. This effectively addresses the low coverage of purely syntactic MT without discarding syntactic information. Further, we show the potential for improved translation results with the inclusion of a syntactic grammar. We also introduce a new syntax-prioritized technique for combining syntactic and non-syntactic phrases that reduces overall phrase table size and decoding time by 61%, with only a minimal drop in automatic translation metric scores. © 2009 Association for Computational Linguistics

关键词： Syntactics

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Vector space models for phrase-based machine translation 8

Vector space models for phrase-based machine translation

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8th workshop on syntax, semantics and structure in statistical translation, SSST 2014

作者： Alkhouli, Tamer Guta, Andreas Ney, Hermann Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen Germany Spoken Language Processing Group Univ. Paris-Sud France LIMSI/CNRS Orsay France

ISBN: (纸本)9781937284961

This paper investigates the application of vector space models (VSMs) to the standard phrase-based machine translation pipeline. VSMs are models based on continuous word representations embedded in a vector space. We exploit word vectors to augment the phrase table with new inferred phrase pairs. This helps reduce out-of-vocabulary (OOV) words. In addition, we present a simple way to learn bilingually-constrained phrase vectors. The phrase vectors are then used to provide additional scoring of phrase pairs, which fits into the standard log-linear framework of phrase-based statistical machine translation. Both methods result in significant improvements over a competitive in-domain baseline applied to the Arabic-to-English task of IWSLT 2013. © 2014 Association for Computational Linguistics

关键词： Vectors

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Application of clause alignment for statistical machine translation 6

Application of clause alignment for statistical machine tran...

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6th workshop on syntax, semantics and structure in statistical translation, SSST 2012 at the 50th Annual Meeting of the Association for Computational Linguistics, ACT 2012

作者： Koeva, Svetla Rizov, Borislav Stoyanova, Ivelina Leseva, Svetlozara Dekova, Rositsa Genov, Angel Tarpomanova, Ekaterina Dimitrova, Tsvetana Kukova, Hristina Department of Computational Linguistics Institute for Bulgarian Language Bulgarian Academy of Sciences Sofia1113 Bulgaria

ISBN: (纸本)9781937284381

The paper presents a new resource light flexible method for clause alignment which combines the Gale-Church algorithm with internally collected textual information. The method does not resort to any pre-developed linguistic resources which makes it very appropriate for resource light clause alignment. We experiment with a combination of the method with the original Gale-Church algorithm (1993) applied for clause alignment. The performance of this flexible method, as it will be referred to hereafter, is measured over a specially designed test corpus. The clause alignment is explored as means to provide improved training data for the purposes of statistical Machine translation (SMT). A series of experiments with Moses demonstrate ways to modify the parallel resource and effects on translation quality: (1) baseline training with a Bulgarian-English parallel corpus aligned at sentence level;(2) training based on parallel clause pairs;(3) training with clause reordering, where clauses in each source language (SL) sentence are reordered according to order of the clauses in the target language (TL) sentence. Evaluation is based on BLEU score and shows small improvement when using the clause aligned corpus. © 2012 Association for Computational Linguistics.

关键词： Computer aided language translation

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