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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41-50 订阅

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A Performance Study of Cube Pruning for Large-Scale Hierarchical Machine translation 7

A Performance Study of Cube Pruning for Large-Scale Hierarch...

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

作者： Huck, Matthias Vilar, David Freitag, Markus Ney, Hermann Human Language Technology and Pattern Recognition Group Rwth Aachen University AachenD-52056 Germany Dfki GmbH Alt-Moabit 91c BerlinD-10559 Germany

ISBN: (纸本)9781937284473

In this paper, we empirically investigate the impact of critical configuration parameters in the popular cube pruning algorithm for decoding in hierarchical statistical machine translation. Specifically, we study how the choice of the k-best generation size affects translation quality and resource requirements in hierarchical search. We furthermore examine the influence of two different granularities of hypothesis recombination. Our experiments are conducted on the large-scale Chinese!English and Arabic!English NIST translation tasks. Besides standard hierarchical grammars, we also explore search with restricted recursion depth of hierarchical rules based on shallow-1 grammars. ©2013 Association for Computational Linguistics.

关键词： Computer aided language translation

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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

ISBN: (纸本)9781932432992

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, virtual nodes, and multiple tree decompositions in the extraction process. At decoding time, we improve automatic metric scores by significantly increasing the number of phrase pairs that match a given test set, while our experiments with hierarchical grammar filtering indicate that more intelligent filtering schemes will also provide a key to future gains. © 2011 Association for Computational Linguistics

关键词： Extraction

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Empirical lower bounds on alignment error rates in syntax-based machine translation 3

Empirical lower bounds on alignment error rates in syntax-ba...

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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： Søgaard, Anders Kuhn, Jonas Center for Language Technology University of Copenhagen Denmark Dpt. of Linguistics University of Potsdam Germany

ISBN: (纸本)9781932432398

The empirical adequacy of synchronous context-free grammars of rank two (2-SCFGs) (Satta and Peserico, 2005), used in syntax-based machine translation systems such as Wu (1997), Zhang et al. (2006) and Chiang (2007), in terms of what alignments they induce, has been discussed in Wu (1997) and Wellington et al. (2006), but with a one-sided focus on so-called "inside-out alignments". Other alignment configurations that cannot be induced by 2-SCFGs are identified in this paper, and their frequencies across a wide collection of hand-aligned parallel corpora are examined. Empirical lower bounds on two measures of alignment error rate, i.e. the one introduced in Och and Ney (2000) and one where only complete translation units are considered, are derived for 2-SCFGs and related formalisms. © 2009 Association for Computational Linguistics

关键词： Alignment

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Using domain-specific and collaborative resources for term translation 6

Using domain-specific and collaborative resources for term t...

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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： Arcan, Mihael Buitelaar, Paul Federmann, Christian Unit for Natural Language Processing Digital Enterprise Research Institute Galway Ireland Language Technology Lab German Research Center for AI Saarbrücken Germany

ISBN: (纸本)9781937284381

In this article we investigate the translation of terms from English into German and vice versa in the isolation of an ontology vocabulary. For this study we built new domain-specific resources from the translation search engine Linguee and from the online encyclopedia Wikipedia. We learned that a domain-specific resource produces better results than a bigger, but more general one. The first finding of our research is that the vocabulary and the structure of the parallel corpus are important. By integrating the multilingual knowledge base Wikipedia, we further improved the translation wrt. the domain-specific resources, whereby some translation evaluation metrics outperformed the results of Google Translate. This finding leads us to the conclusion that a hybrid translation system, a combination of bilingual terminological resources and statistical machine translation can help to improve translation of domain-specific terms. © 2012 Association for Computational Linguistics.

关键词： Search engines

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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

ISBN: (纸本)9781932432992

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 indicated that dissociating semantic roles and fillers from their predicates actually improves correlation with human adequacy judgments even though, intuitively, properly segregating event frames should more accurately reflect the preservation of meaning. Our analysis finds that both properly structured and flattened representations fail to adequately account for the contribution of each semantic frame to the overall sentence. We then show that the correlation of HMEANT, the human variant of MEANT, can be greatly improved by introducing a simple length-based weighting scheme that approximates the degree of contribution of each semantic frame to the overall sentence. The new results also show that, without flattening the structure of semantic frames, weighting the degree of each frame’s contribution gives HMEANT higher correlations than the previously best-performing flattened model, as well as HTER. © 2011 Association for Computational Linguistics

关键词： semantics

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The influence of argument structure on semantic role assignment

The influence of argument structure on semantic role assignm...

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2004 Conference on Empirical Methods in Natural Language Processing, EMNLP 2004

作者： Padó, Sebastian Boleda, Gemma SALSA Dept. of Computational Linguistics Saarland University Saarbrücken Germany GLiCom Dept. of Translation and Interpreting Pompeu Fabra University Barcelona Spain

We present a data and error analysis for semantic role labelling. In a first experiment, we build a generic statistical model for semantic role assignment in the FrameNet paradigm and show that there is a high variance in performance across frames. The main hypothesis of our paper is that this variance is to a large extent a result of differences in the underlying argument structure of the predicates in different frames. In a second experiment, we show that frame uniformity, which measures argument structure variation, correlates well with the performance figures, effectively explaining the variance. © 2005 Association for Computational Linguistics

关键词： semantics

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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

ISBN: (纸本)9781932432992

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 into account the distortion effect in the priors. In addition to that we propose multiple novel distortion features based on syntactic parsing. A new metric is also introduced to measure the effect of distortion in the translation hypotheses. We show that both smoothed priors and syntax-based features help to significantly improve the reordering and hence the translation performance on a large-scale Chinese-to-English machine translation task.

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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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proceedings of the fifth workshop on syntax, semantics and structure in statistical translation

作者： Greg Hanneman Alon Lavie Carnegie Mellon University Pittsburgh PA

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.

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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

ISBN: (纸本)9781932432992

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 to adapt these systems to new languages. However, we show that the nature of these resources is significantly different from the "free-text" paradigm used to train most statistical machine translation systems. In particular, we see significant differences in the linguistic nature of these resources and such resources have rich additional semantics. We demonstrate that as a result of these linguistic differences, standard SMT methods, in particular evaluation metrics, can produce poor performance. We then look to the task of leveraging these semantics for translation, which we approach in three ways: by adapting the translation system to the domain of the resource; by examining if semantics can help to predict the syntactic structure used in translation; and by evaluating if we can use existing translated taxonomies to disambiguate translations. We present some early results from these experiments, which shed light on the degree of success we may have with each approach.

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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

ISBN: (纸本)9781932432992

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 translation options and for reordering them. Decoding is done by translating each node in the tree and combining its translations with those of its head in alternative orders with respect to its siblings. Reordering of the siblings exploits a heuristic based on the syntactic information from the parse tree which is learned from the corpus. The decoder uses the same phrase tables produced by a PBT system for looking up translations of single words or of partial sub-trees. A mathematical model is presented and experimental results are discussed.

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