Training word alignment models on large corpora is a very time-consuming processes. This paper describes two parallel implementations of GIZA++ that accelerate this word alignment process. One of the implementations runs on computer clusters, the other runs on multi-processor system using multi-threading technology. Results show a near-linear speedup according to the number of CPUs used, and alignment quality is preserved.
mGIZA++ is a parallel implementation of the IBM and HMM models REF .
Parallel Implementations of Word Alignment Tool
Software Engineering, Testing, and Quality Assurance for Natural Language Processing
Computer Science