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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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Improving phrase-based translation via word alignments from stochastic inversion transduction grammars 3

Improving phrase-based translation via word alignments from ...

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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： Saers, Markus Wu, Dekai Dept. of Linguistics and Philology Uppsala University Sweden Human Language Technology Center Dept. of Computer Science and Engineering HKUST Hong Kong

ISBN: (纸本)9781932432398

We argue that learning word alignments through a compositionally-structured, joint process yields higher phrase-based translation accuracy than the conventional heuristic of intersecting conditional models. Flawed word alignments can lead to flawed phrase translations that damage translation accuracy. Yet the IBM word alignments usually used today are known to be flawed, in large part because IBM models (1) model reordering by allowing unrestricted movement of words, rather than constrained movement of compositional units, and therefore must (2) attempt to compensate via directed, asymmetric distortion and fertility models. The conventional heuristics for attempting to recover from the resulting alignment errors involve estimating two directed models in opposite directions and then intersecting their alignments - to make up for the fact that, in reality, word alignment is an inherently joint relation. A natural alternative is provided by Inversion Transduction Grammars, which estimate the joint word alignment relation directly, eliminating the need for any of the conventional heuristics. We show that this alignment ultimately produces superior translation accuracy on BLEU, NIST, and METEOR metrics over three distinct language pairs. © 2009 Association for Computational Linguistics

关键词： Alignment

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Chunk-Based Dependency-to-String Model with Japanese Case Frame 10

Chunk-Based Dependency-to-String Model with Japanese Case Fr...

引用

10th China workshop on Machine translation (CWMT)

作者： Xu, Jinan Wu, Peihao Xie, Jun Zhang, Yujie Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China Beijing Samsung Telecom R&D Ctr Beijing 100028 Peoples R China

ISBN: (纸本)9783662457016;9783662457009

This paper proposes an idea to integrate Japanese case frame into chunk-based dependency-to-string model. At first, case frames are acquired from Japanese chunk-based dependency analysis results. Then case frames are used to constraint rule extraction and decoding in chunk-based dependency-to-string model. Experimental results show that the proposed method performs well on long structural reordering and lexical translation, and achieves better performance than hierarchical phrase-based model and word-based dependency-to-string model on Japanese to Chinese test sets.

关键词： statistical Machine translation Japanese Case Frame syntax structure chunk-based dependency-to-string model

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Linguistically-Enriched Models for Bulgarian-to-English Machine translation 12

Linguistically-Enriched Models for Bulgarian-to-English Mach...

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workshop on syntax and structure in statistical translation

作者： Rui Wang Petya Osenova Kiril Simov Language Technology Lab DFKI GmbH Saarbriicken Germany Linguistic Modelling Department IICT Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (纸本)9781627483452

In this paper, we present our linguistically-enriched Bulgarian-to-English statistical machine translation model, which takes a statistical machine translation (SMT) system as backbone various linguistic features as factors. The motivation is to take advantages of both the robustness of the SMT system and the rich linguistic knowledge from morphological analysis as well as the hand-crafted grammar resources. The automatic evaluation has shown promising results and our extensive manual analysis confirms the high quality of the translation the system delivers. The whole framework is also extensible for incorporating information provided by different sources.

关键词： machine translation EXPANDABLE Surface mount technology Linguistics translation systems

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Enriching Parallel Corpora for statistical Machine translation with Semantic Negation Rephrasing 12

Enriching Parallel Corpora for Statistical Machine Translati...

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workshop on syntax and structure in statistical translation

作者： Dominikus Wetzel Francis Bond Department of Computational Linguistics Saarland University Linguistics and Multilingual Studies Nanyang Technological University

ISBN: (纸本)9781627483452

This paper presents an approach to improving performance of statistical machine translation by automatically creating new training data for difficult to translate phenomena. In particular this contribution is targeted towards tackling the poor performance of a state-of-the-art system on negated sentences. The corpus expansion is achieved by high quality rephrasing of existing sentences to their negated counterparts making use of semantic transfer. The method is designed to work on both sides of the parallel corpus while preserving the alignment. Our results show an overall improvement of 0.16 BLEU points, with a statistically significant increase of 1.63 BLEU points when tested on only negated test data.

关键词： machine translation Semantics Belgo-Luxembourg Economic Union Negation Parallel Lines sidings observational data

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Using Domain-specific and Collaborative Resources for Term translation 12

Using Domain-specific and Collaborative Resources for Term T...

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workshop on syntax and structure in statistical translation

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

ISBN: (纸本)9781627483452

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.

关键词： translations translation machine translation translation Process Vocabulary Wikipedia English English language

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Head Finalization Reordering for Chinese-to-Japanese Machine translation 12

Head Finalization Reordering for Chinese-to-Japanese Machine...

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workshop on syntax and structure in statistical translation

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

ISBN: (纸本)9781627483452

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.

关键词： machine translation Language Belgo-Luxembourg Economic Union translations translation DECODING Rule translation Process translation systems HPSG(head-driven phrase structure grammar)

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Improving statistical Machine translation through co-joining parts of verbal constructs in English-Hindi translation 12

Improving Statistical Machine Translation through co-joining...

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workshop on syntax and structure in statistical translation

作者： Karunesh Kumar Arora R Mahesh K Sinha 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)9781627483452

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.

关键词： machine translation translations translation Object oriented programming languages translation Process Adjudication Verbal Fluency Language

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Zero Pronoun Resolution can Improve the Quality of J-E translation 12

Zero Pronoun Resolution can Improve the Quality of J-E Trans...

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workshop on syntax and structure in statistical translation

作者： Hirotoshi Taira Katsuhito Sudoh Masaaki Nagata NTT Communication Science Laboratories 2-4 Hikaridai Seika-cho Keihanna Science City Kyoto 619-0237 Japan

ISBN: (纸本)9781627483452

In Japanese, particularly, spoken Japanese, subjective, objective and possessive cases are very often omitted. Such Japanese sentences are often translated by Japanese-English statistical machine translation to the English sentence whose subjective, objective and possessive cases are omitted, and it causes to decrease the quality of translation. We performed experiments of J-E phrase based translation using Japanese sentence, whose omitted pronouns are complemented by human. We introduced 'antecedent F-measure' as a score for measuring quality of the translated English. As a result, we found that it improves the scores of antecedent F-measure while the BLEU scores were almost unchanged. Every effectiveness of the zero pronoun resolution differs depending on the type and case of each zero pronoun.

关键词： Pronouns translations translation machine translation Zero translation Process Resolving power English language English Japanese Belgo-Luxembourg Economic Union

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Towards a Predicate-Argument Evaluation for MT 12

Towards a Predicate-Argument Evaluation for MT

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workshop on syntax and structure in statistical translation

作者： Ondrej Bojar Dekai Wu Charles University in Prague Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics HKUST Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9781627483452

HMEANT (Lo and Wu, 2011a) is a manual MT evaluation technique that focuses on predicate-argument structure of the sentence. We relate HMEANT to an established linguistic theory, highlighting the possibilities of reusing existing knowledge and resources for interpreting and automating HMEANT. We apply HMEANT to a new language, Czech in particular, by evaluating a set of English-to-Czech MT systems. HMEANT proves to correlate with manual rankings at the sentence . level better than a range of automatic metrics. However, the main contribution of this paper is the identification of several issues of HMEANT annotation and our proposal on how to resolve them.

关键词： machine translation MT Linguistic Theory Probability manual evaluation method Adjudication Automation

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