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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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A study of translation rule classification for syntax-based statistical machine translation 09

A study of translation rule classification for syntax-based ...

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proceedings of the third workshop on syntax and structure in statistical translation

作者： Hongfei Jiang Sheng Li Muyun Yang Tiejun Zhao Harbin Institute of Technology

ISBN: (纸本)9781932432398

Recently, numerous statistical machine translation models which can utilize various kinds of translation rules are proposed. In these models, not only the conventional syntactic rules but also the non-syntactic rules can be applied. Even the pure phrase rules are includes in some of these models. Although the better performances are reported over the conventional phrase model and syntax model, the mixture of diversified rules still leaves much room for study. In this paper, we present a refined rule classification system. Based on this classification system, the rules are classified according to different standards, such as lexicalization level and generalization. Especially, we refresh the concepts of the structure reordering rules and the discontiguous phrase rules. This novel classification system may supports the SMT research community with some helpful references.

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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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syntax-oriented evaluation measures for machine translation output 09

Syntax-oriented evaluation measures for machine translation ...

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proceedings of the Fourth workshop on statistical Machine translation

作者： Maja Popović Hermann Ney RWTH Aachen University Aachen Germany

We explored novel automatic evaluation measures for machine translation output oriented to the syntactic structure of the sentence: the Bleu score on the detailed Part-of-Speech (pos) tags as well as the precision, recall and F-measure obtained on pos n-grams. We also introduced F-measure based on both word and pos n-grams. Correlations between the new metrics and human judgments were calculated on the data of the first, second and third shared task of the statistical Machine translation workshop. Machine translation outputs in four different European languages were taken into account: English, Spanish, French and German. The results show that the new measures correlate very well with the human judgements and that they are competitive with the widely used BLEU, METEOR and TER metrics.

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Decoding with syntactic and non-syntactic phrases in a syntax-based machine translation system 09

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

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proceedings of the third workshop on syntax and structure in statistical translation

作者： Greg Hanneman Alon Lavie Carnegie Mellon University Pittsburgh PA

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.

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Coupling hierarchical word reordering and decoding in phrase-based statistical machine translation 09

Coupling hierarchical word reordering and decoding in phrase...

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proceedings of the third workshop on syntax and structure in statistical translation

作者： Maxim Khalilov José A. R. Fonollosa Mark Dras Universitat Politèicnica de Catalunya Barcelona Spain Macquarie University Sydney 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.

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Empirical lower bounds on alignment error rates in syntax-based machine translation 09

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

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proceedings of the third workshop on syntax and structure in statistical translation

作者： Anders Søgaard Jonas Kuhn University of Copenhagen University of Potsdam

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.

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Using syntax to improve word alignment precision for syntax-based machine translation 08

Using syntax to improve word alignment precision for syntax-...

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proceedings of the third workshop on statistical Machine translation

作者： Victoria Fossum Kevin Knight Steven Abney University of Michigan Ann Arbor MI University of Southern California Marina del Rey CA

ISBN: (纸本)9781932432091

Word alignments that violate syntactic correspondences interfere with the extraction of string-to-tree transducer rules for syntax-based machine translation. We present an algorithm for identifying and deleting incorrect word alignment links, using features of the extracted rules. We obtain gains in both alignment quality and translation quality in Chinese-English and Arabic-English translation experiments relative to a GIZA++ union baseline.

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A walk on the other side: adding statistical components to a transfer-based translation system 07

A walk on the other side: adding statistical components to a...

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proceedings of the NAACL-HLT 2007/AMTA workshop on syntax and structure in statistical translation

作者： Ariadna Font Llitjós Stephan Vogel Carnegie Mellon University Pittsburgh PA

This paper seeks to complement the current trend of adding more structure to statistical Machine translation systems, by exploring the opposite direction: adding statistical components to a Transfer-Based MT system. Initial results on the BTEC data show significant improvement according to three automatic evaluation metrics (BLEU, NIST and METEOR).

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