Work

A syntax-based statistical translation model

Year: 2001

Type: conference-paper

Abstract: We present a syntax-based statistical translation model.Our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each node.These operations capture linguistic differences such as word order and case marking.Model parameters are estimated in polynomial time using an EM algorithm.The model produces word alignments that are better than those produced by IBM Model 5.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.3115/1073012.1073079

Authors: Kenji Yamada, Kevin Knight

Institution: University of Southern California

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Defense Advanced Research Projects Agency

OpenAlex ID: W2116316001

FWCI: 18.71

Cites: 313

Cited by: 728

Related to: 10