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Cited by 379

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Dependency treelet translation: syntactically informed phrasal SMT

Open access
Quirk, Chris, Menezes, Arul, Cherry, Colin·2005·Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05

Abstract

We describe a novel approach to statistical machine translation that combines syntactic information in the source language with recent advances in phrasal translation. This method requires a source-language dependency parser, target language word segmentation and an unsupervised word alignment component. We align a parallel corpus, project the source dependency parse onto the target sentence, extract dependency treelet translation pairs, and train a tree-based ordering model. We describe an efficient decoder and show that using these tree-based models in combination with conventional SMT models provides a promising approach that incorporates the power of phrasal SMT with the linguistic generality available in a parser.

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Metadata

Authors
Quirk, C., Menezes, A., & Cherry, C.
Venue
Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05
Published
2005
Pages
271-279
OpenAlex
W2153800732
Cited by
379
References
28
FWCI
28.38
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Dependency treelet translation: syntactically informed phrasal SMT. https://app.cochat.ai/papers/10.3115/1219840.1219874
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Quirk, C., Menezes, A., & Cherry, C. (2005). Dependency treelet translation: syntactically informed phrasal SMT. Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05. https://doi.org/10.3115/1219840.1219874

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.