Conference Publication Details
Mandatory Fields
Tinsley, J;Hearne, M;Way, A
COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING
Exploiting Parallel Treebanks to Improve Phrase-Based Statistical Machine Translation
2009
January
Published
1
2 ()
Optional Fields
318
331
Given much recent discussion and the shift in focus of the field, it is becoming apparent that the incorporation of syntax is the way forward for the current state-of-the-art in machine translation (MT). Parallel treebanks are a relatively recent innovation and appear to be ideal candidates for NIT training material. However. until recently there has been no other means to build them than by hand. In this paper, we describe how we make use of new tools to automatically build a large parallel treebank and extract a set of linguistically motivated phrase pairs from it. We show that adding these phrase pairs to the translation model of a baseline phrase-based statistical NIT (PBSMT) system leads to significant improvements in translation quality. We describe further experiments on incorporating parallel treebank information into PBSMT, such as word alignments. We investigate the conditions under which the incorporation of parallel treebank data performs optimally. Finally. we discuss the potential of parallel treebanks in other paradigms of MT.
Grant Details