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Learning Machine Translation$
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Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster

Print publication date: 2008

Print ISBN-13: 9780262072977

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262072977.001.0001

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Discriminative Phrase Selection for SMT

Discriminative Phrase Selection for SMT

(p.205) 11 Discriminative Phrase Selection for SMT
Learning Machine Translation

Jesús Giménez

Lluís Màrquez

The MIT Press

This chapter explores the application of discriminative learning to the problem of phrase selection in statistical machine translation (SMT). The chapter is organized as follows. Section 11.2 describes previous and current approaches to dedicated word selection. Section 11.3 describes the approach to discriminative phrase translation (DPT). It presents experimental results on the application of DPT models to the Spanish-to-English translation of European Parliament proceedings. In Section 11.4, prior to considering the full translation task, it measures the local accuracy of DPT classifiers at the isolated phrase translation task in which the goal is not to translate the whole sentence but only individual phrases without having to integrate their translations in the context of the target sentence. Section 11.5 tackles the full translation task while Section 11.6 summarizes the main conclusions.

Keywords:   phrase selection, statistical machine translation, discriminative learning, word selection

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