Integrating source-language context into phrase-based statistical machine translation

R. Haque, S.K. Naskar, A. van den Bosch, A. Way

    Research output: Contribution to journalArticleScientificpeer-review

    13 Citations (Scopus)


    The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling directly into log-linear PB-SMT can positively influence the weighting and selection of target phrases, and thus improve translation quality. In this contribution we present a revised, extended account of our previous work on using a range of contextual features, including lexical features of neighbouring words, supertags, and dependency information. We add a number of novel aspects, including the use of semantic roles as new contextual features in PB-SMT, adding new language pairs, and examining the scalability of our research to larger amounts of training data. While our results are mixed across feature selections, classifier hyperparameters, language pairs, and learning curves, we observe that including contextual features of the source sentence in general produces improvements. The most significant improvements involve the integration of long-distance contextual features, such as dependency relations in combination with part-of-speech tags in Dutch-to-English subtitle translation, the combination of dependency parse and semantic role information in English-to-Dutch parliamentary debate translation, or supertag features in English-to-Chinese translation.
    Original languageEnglish
    Pages (from-to)239-285
    Number of pages47
    JournalMachine Translation
    Issue number3
    Publication statusPublished - 2011


    Dive into the research topics of 'Integrating source-language context into phrase-based statistical machine translation'. Together they form a unique fingerprint.

    Cite this