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syntax and semantics in quality estimation of machine translation 8

Syntax and semantics in quality estimation of machine transl...

引用

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

作者： Kaljahi, Rasoul Foster, Jennifer Roturier, Johann NCLT School of Computing Dublin City University Ireland Symantec Research Labs Dublin Ireland

ISBN: (纸本)9781937284961

We employ syntactic and semantic information in estimating the quality of machine translation from a new data set which contains source text from English customer support forums and target text consisting of its machine translation into French. These translations have been both post-edited and evaluated by professional translators. We find that quality estimation using syntactic and semantic information on this data set can hardly improve over a baseline which uses only surface features. However, the performance can be improved when they are combined with such surface features. We also introduce a novel metric to measure translation adequacy based on predicate-argument structure match using word alignments. While word alignments can be reliably used, the two main factors affecting the performance of all semantic-based methods seems to be the low quality of semantic role labelling (especially on ill-formed text) and the lack of nominal predicate annotation. © 2014 Association for Computational Linguistics

关键词： Machine translation

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Utilizing target-side semantic role labels to assist hierarchical phrase-based machine translation 5

Utilizing target-side semantic role labels to assist hierarc...

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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： Gao, Qin Vogel, Stephan Language Technologies Institute Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States

ISBN: (纸本)9781932432992

In this paper we present a novel approach of utilizing Semantic Role Labeling (SRL) information to improve Hierarchical Phrase-based Machine translation. We propose an algorithm to extract SRL-aware Synchronous Context-Free Grammar (SCFG) rules. Conventional Hiero-style SCFG rules will also be extracted in the same framework. Special conversion rules are applied to ensure that when SRL-aware SCFG rules are used in derivation, the decoder only generates hypotheses with complete semantic structures. We perform machine translation experiments using 9 different Chinese-English test-sets. Our approach achieved an average BLEU score improvement of 0.49 as well as 1.21 point reduction in TER. © 2011 Association for Computational Linguistics

关键词： Semantics

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Overcoming the curse of sentence length for neural machine translation using automatic segmentation 8

Overcoming the curse of sentence length for neural machine t...

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

作者： Pouget-Abadie, Jean Bahdanau, Dzmitry van Merriënboer, Bart Cho, Kyunghyun Bengio, Yoshua Ecole Polytechnique France Jacobs University Bremen Germany Université de Montréal Canada

ISBN: (纸本)9781937284961

The authors of (Cho et al., 2014a) have shown that the recently introduced neural network translation systems suffer from a significant drop in translation quality when translating long sentences, unlike existing phrase-based translation systems. In this paper, we propose a way to address this issue by automatically segmenting an input sentence into phrases that can be easily translated by the neural network translation model. Once each segment has been independently translated by the neural machine translation model, the translated clauses are concatenated to form a final translation. Empirical results show a significant improvement in translation quality for long sentences. © 2014 Association for Computational Linguistics

关键词： Neural machine translation

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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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Coupling hierarchical word reordering and decoding in phrase-based statistical machine translation 3

Coupling hierarchical word reordering and decoding in phrase...

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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： Khalilov, Maxim Fonollosa, José A.R. Dras, Mark Universitat Politècnica de Catalunya Campus Nord UPC Barcelona08034 Spain Macquarie University North Ryde NSW Sydney2109 Australia

ISBN: (纸本)9781932432398

In this paper, we start with the existing idea of taking reordering rules automatically derived from syntactic representations, and applying them in a preprocessing step before translation to make the source sentence structurally more like the target;and we propose a new approach to hierarchically extracting these rules. We evaluate this, combined with a lattice-based decoding, and show improvements over state-of-the-art distortion models. © 2009 Association for Computational Linguistics

关键词： Decoding

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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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Multiple reorderings in phrase-based machine translation 2

Multiple reorderings in phrase-based machine translation

引用

2nd workshop on syntax and structure in statistical translation, SSST 2008

作者： Ge, Niyu Ittycheriah, Abe Papineni, Kishore IBM T.J.Watson Research 1101 Kitchawan Rd Yorktown HeightsNY10598 United States Yahoo! Research 45 West 18th St. New YorkNY10011 United States

ISBN: (纸本)9781932432169

This paper presents a method to integrate multiple reordering strategies in phrase-based statistical machine translation. Recently there has been much research effort in reordering problems in machine translation. State-of-the-art decoders incorporate sophisticated local reordering strategies, but there is little research on a unified approach to incorporate various kinds of reordering methods. We present a phrase-based decoder which easily allows multiple reordering schemes. We show how to use this framework to perform distance-based reordering and HIERO-style (Chiang 2005) hierarchical reordering. We also present two novel syntax-based reordering methods, one built on part-of-speech tags and the other based on parse trees. We will give experimental results using these relatively easy to implement methods on standard tests. © 2008 Association for Computational Linguistics

关键词： Machine translation

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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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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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Combining morphosyntactic enriched representation with n-best reranking in statistical translation

Combining morphosyntactic enriched representation with n-bes...

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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： Bonneau-Maynard, H. Allauzen, A. Déchelotte, D. Schwenk, H. Spoken Language Processing Group LIMSI-CNRS BP 133 Orsay Cedex91403 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 using morphosyntactic categories, n-best hypotheses reranking, and the combination of both methods with word or morphosyntactic n-gram language model reranking. Experiments are carried out on the English-to-Spanish translation task. Using the morphosyntactic language model alone does not results in any improvement in performance. However, combining morphosyntactic word disambiguation with a word based 4-gram language model results in a relative improvement in the BLEU score of 2.3% on the development set and 1.9% on the test set. © 2007 Association for Computational Linguistics

关键词： translation (languages)

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Generation in machine translation from deep syntactic trees

Generation in machine translation from deep syntactic trees

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作者： Hall, Keith Němec, Petr Center for Language and Speech Processing Johns Hopkins University BaltimoreMD21218 United States Institute of Formal and Applied Linguistics 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 machine translation and paraphrasing of speech transcripts. In an effort to validate one such formalism of deep syntax, the Praguian Tectogrammatical Representation (TR), we present a model of synthesis for English which generates surface-syntactic trees as well as strings. We propose a generative model for function word insertion (prepositions, definite/indefinite articles, etc.) and sub-phrase reordering. We show by way of empirical results that this model is effective in constructing acceptable English sentences given impoverished trees. © 2007 Association for Computational Linguistics

关键词： Syntactics

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