Scalable inference and training of context-rich syntactic translation models

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Scalable inference and training of context-rich syntactic translation models (2006)

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by Michel Galley , Jonathan Graehl , Kevin Knight , Daniel Marcu , Steve Deneefe , Wei Wang , Ignacio Thayer

Venue:	In ACL
Citations:	280 - 21 self

BibTeX

@INPROCEEDINGS{Galley06scalableinference,
    author = {Michel Galley and Jonathan Graehl and Kevin Knight and Daniel Marcu and Steve Deneefe and Wei Wang and Ignacio Thayer},
    title = {Scalable inference and training of context-rich syntactic translation models},
    booktitle = {In ACL},
    year = {2006},
    pages = {961--968}
}

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Abstract

Statistical MT has made great progress in the last few years, but current translation models are weak on re-ordering and target language fluency. Syntactic approaches seek to remedy these problems. In this paper, we take the framework for acquiring multi-level syntactic translation rules of (Galley et al., 2004) from aligned tree-string pairs, and present two main extensions of their approach: first, instead of merely computing a single derivation that minimally explains a sentence pair, we construct a large number of derivations that include contextually richer rules, and account for multiple interpretations of unaligned words. Second, we propose probability estimates and a training procedure for weighting these rules. We contrast different approaches on real examples, show that our estimates based on multiple derivations favor phrasal re-orderings that are linguistically better motivated, and establish that our larger rules provide a 3.63 BLEU point increase over minimal rules. 1

Keyphrases

scalable inference context-rich syntactic translation model syntactic approach different approach phrasal re-orderings unaligned word large number last year tree-string pair great progress single derivation sentence pair bleu point increase probability estimate current translation model real example multi-level syntactic translation rule multiple interpretation main extension multiple derivation statistical mt target language fluency minimal rule training procedure

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