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Context-dependent SMT model using bilingual verb-noun collocation

Authors:

Young-Sook Hwang,

Yutaka SasakiAuthors Info & Claims

ACL '05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

Pages 549 - 556

https://doi.org/10.3115/1219840.1219908

Published: 25 June 2005 Publication History

Abstract

In this paper, we propose a new context-dependent SMT model that is tightly coupled with a language model. It is designed to decrease the translation ambiguities and efficiently search for an optimal hypothesis by reducing the hypothesis search space. It works through reciprocal incorporation between source and target context: a source word is determined by the context of previous and corresponding target words and the next target word is predicted by the pair consisting of the previous target word and its corresponding source word. In order to alleviate the data sparseness in chunk-based translation, we take a stepwise back-off translation strategy. Moreover, in order to obtain more semantically plausible translation results, we use bilingual verb-noun collocations; these are automatically extracted by using chunk alignment and a monolingual dependency parser. As a case study, we experimented on the language pair of Japanese and Korean. As a result, we could not only reduce the search space but also improve the performance.

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Cited By

Chakraborty TPal SMondal TSaikh TBandyopadhyay SBiemann CGiesbrecht E(2011)Measuring the compositionality of bigrams using statistical methodologiesProceedings of the Workshop on Distributional Semantics and Compositionality10.5555/2043121.2043128(38-42)Online publication date: 24-Jun-2011
https://dl.acm.org/doi/10.5555/2043121.2043128
Venkatapathy SJoshi AMooney R(2005)Measuring the relative compositionality of verb-noun (V-N) collocations by integrating featuresProceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing10.3115/1220575.1220688(899-906)Online publication date: 6-Oct-2005
https://dl.acm.org/doi/10.3115/1220575.1220688

Context-dependent SMT model using bilingual verb-noun collocation
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Hardware
  1. Power and energy
    1. Power estimation and optimization

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ACL '05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

June 2005

657 pages

General Chair:
Kevin Knight
University of Southern California

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Association for Computational Linguistics

United States

Publication History

Published: 25 June 2005

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ACL '05 Paper Acceptance Rate 77 of 423 submissions, 18%;

Overall Acceptance Rate 85 of 443 submissions, 19%

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Cited By

Chakraborty TPal SMondal TSaikh TBandyopadhyay SBiemann CGiesbrecht E(2011)Measuring the compositionality of bigrams using statistical methodologiesProceedings of the Workshop on Distributional Semantics and Compositionality10.5555/2043121.2043128(38-42)Online publication date: 24-Jun-2011
https://dl.acm.org/doi/10.5555/2043121.2043128
Venkatapathy SJoshi AMooney R(2005)Measuring the relative compositionality of verb-noun (V-N) collocations by integrating featuresProceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing10.3115/1220575.1220688(899-906)Online publication date: 6-Oct-2005
https://dl.acm.org/doi/10.3115/1220575.1220688

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