Standard phrase-based statistical machine translation systems generate translations based on an inventory of continuous bilingual phrases. In this work, we extend a phrase-based decoder with the ability to make use of phrases that are discontinuous in the source part. Our dynamic programming beam search algorithm supports separate pruning of coverage hypotheses per cardinality and of lexical hypotheses per coverage, as well as coverage constraints that impose restrictions on the possible reorderings. In addition to investigating these aspects, which are related to the decoding procedure, we also concentrate our attention on the question of how to obtain source-side discontinuous phrases from parallel training data. Two approaches (hierarchical and discontinuous extraction) are presented and compared. On a large-scale Chinese!English translation task, we conduct a thorough empirical evaluation in order to study a number of system configurations with source-side discontinuous phrases, and to compare them to setups which employ continuous phrases only.
Matthias Huck, Jan-Thorsten Peter, Markus Freitag, Stephan Peitz and Hermann Ney
Hierarchical Phrase-Based Translation with Jane 2
In this paper, we give a survey of several recent extensions to hierarchical phrase-based machine translation that have been implemented in version 2 of Jane, RWTH's open source statistical machine translation toolkit. We focus on the following techniques: Insertion and deletion models, lexical scoring variants, reordering extensions with non-lexicalized reordering rules and with a discriminative lexicalized reordering model, and soft string-to-dependency hierarchical machine translation. We describe the fundamentals of each of these techniques and present experimental results obtained with Jane 2 to confirm their usefulness in state-of-the-art hierarchical phrase-based translation (HPBT).
Daniel Stein, David Vilar, Stephan Peitz, Markus Freitag, Matthias Huck and Hermann Ney
A Guide to Jane, an Open Source Hierarchical Translation Toolkit
Jane is RWTH's hierarchical phrase-based translation toolkit. It includes tools for phrase extraction, translation and scaling factor optimization, with efficient and documented programs of which large parts can be parallelized. The decoder features syntactic enhancements, reorderings, triplet models, discriminative word lexica, and support for a variety of language model formats. In this article, we will review the main features of Jane and explain the overall architecture. We will also indicate where and how new models can be included.