Accession Number:

ADA558560

Title:

Incremental Syntactic Language Models for Phrase-Based Translation

Descriptive Note:

Conference paper

Corporate Author:

AIR FORCE RESEARCH LAB WRIGHT-PATTERSON AFB OH

Report Date:

2011-06-01

Pagination or Media Count:

13.0

Abstract:

This paper describes a novel technique for incorporating syntactic knowledge into phrase-based machine translation through incremental syntactic parsing. Bottom-up and top-down parsers typically require a completed string as input. This requirement makes it difficult to incorporate them into phrase-based translation, which generates partial hypothesized translations from left-to-right. Incremental syntactic language models score sentences in a similar left-to-right fashion, and are therefore a good mechanism for incorporating syntax into phrase-based translation. We give a formal definition of one such linear-time syntactic language model, detail its relation to phrase-based decoding, and integrate the model with the Moses phrase-based translation system. We present empirical results on a constrained Urdu-English translation task that demonstrate a significant BLEU score improvement and a large decrease in perplexity.

Subject Categories:

  • Linguistics
  • Statistics and Probability
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE