Existing tools for generating phrase tables for phrase-based Statistical Machine Translation (SMT) are generally optimised towards low memory use to allow processing of large corpora with limited memory. Whilst being a reasonable design choice, this approach does not make optimal use of resources when the sufficient memory is available. We present memscore, a new open-source tool to score phrases in memory. Besides acting as a faster drop-in replacement for existing software, it implements a number of standard smoothing techniques and provides a platform for easy experimentation with new scoring methods.
|Pages (from-to)||87 - 96|
|Number of pages||10|
|Journal||Prague Bulletin of Mathematical Linguistics|
|Publication status||Published - 26 Feb 2010|
|Event||4th Machine Translation Marathon - Dublin City University, Dublin, Ireland|
Duration: 25 Jan 2010 → 30 Jan 2010