For presentation clarity we show only a sample of the full set of ten test points though all results follow the pattern that using more aligned sentences to derive our grammar set resulted in slightly better performance versus a restricted training set.
for the same coverage constraints not only do we achieve comparable performance to batch retrained models using the sOEM method of incremental adaptation, we are able to align and adopt new data from the input stream orders of magnitude quicker since we only align the mini-batch of sentences collected from the last epoch.