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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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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 automatically learned from source-side chunks and word alignments. During translation, the rules are used to generate a reordering lattice for each sentence. Experimental results are reported for a Chinese-to-English task, showing an improvement of 0.5%-1.8% BLEU score absolute on various test sets and better computational efficiency than reordering during decoding. The experiments also show that the reordering at the chunk-level performs better than at the POS-level. © 2007 Association for Computational Linguistics

关键词： Computational efficiency

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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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Inversion transduction grammar for joint phrasal translation modeling

Inversion transduction grammar for joint phrasal translation...

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作者： Cherry, Colin Lin, Dekang Department of Computing Science University of Alberta EdmontonABT6G 2E8 Canada Google Inc. 1600 Amphitheatre Parkway Mountain ViewCA9403 United States

We present a phrasal inversion transduction grammar as an alternative to joint phrasal translation models. This syntactic model is similar to its flat-string phrasal predecessors, but admits polynomial-time algorithms for Viterbi alignment and EM training. We demonstrate that the consistency constraints that allow flat phrasal models to scale also help ITG algorithms, producing an 80-times faster inside-outside algorithm. We also show that the phrasal translation tables produced by the ITG are superior to those of the flat joint phrasal model, producing up to a 2.5 point improvement in BLEU score. Finally, we explore, for the first time, the utility of a joint phrasal translation model as a word alignment method. © 2007 Association for Computational Linguistics

关键词： Bacteriophages

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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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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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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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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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Generalizing local translation models 2

Generalizing local translation models

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

作者： Subotin, Michael Laboratory for Computational Linguistics and Information Processing Department of Linguistics University of Maryland College ParkMD20742 United States

ISBN: (纸本)9781932432169

We investigate translation modeling based on exponential estimates which generalize essential components of standard translation models. In application to a hierarchical phrase-based system the simplest generalization allows its models of lexical selection and reordering to be conditioned on arbitrary attributes of the source sentence and its annotation. Viewing these estimates as approximations of sentence-level probabilities motivates further elaborations that seek to exploit general syntactic and morphological patterns. Dimensionality control with1 regularizers makes it possible to negotiate the tradeoff between translation quality and decoding speed. Putting together and extending several recent advances in phrase-based translation we arrive at a flexible modeling framework that allows efficient leveraging of monolingual resources and tools. Experiments with features derived from the output of Chinese and Arabic parsers and an Arabic lemmatizer show significant improvements over a strong baseline. © 2008 Association for Computational Linguistics

关键词： Syntactics

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Dependency-based automatic evaluation for machine translation

Dependency-based automatic evaluation for machine translatio...

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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 treebank-based, wide-coverage, probabilistic Lexical-Functional Grammar (LFG) parser to produce a set of structural dependencies for each translation-reference sentence pair, and then calculates the precision and recall for these dependencies. Our dependency-based evaluation, in contrast to most popular string-based evaluation metrics, will not unfairly penalize perfectly valid syntactic variations in the translation. In addition to allowing for legitimate syntactic differences, we use paraphrases in the evaluation process to account for lexical variation. In comparison with other metrics on 16,800 sentences of Chinese-English newswire text, our method reaches high correlation with human scores. An experiment with two translations of 4,000 sentences from Spanish-English Europarl shows that, in contrast to most other metrics, our method does not display a high bias towards statistical models of translation. © 2007 Association for Computational Linguistics

关键词： Machine translation

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