Dear Moses,
What are the experiences with truecasing v the recaser? It seems the
recaser's default does:
1) Train a truecaser
2) Truecase the monolingual data
3) Train an LM on the truecased data
There's an option to just directly go to LM training. Any thoughts on
which is better?
It just feels weird to use the truecaser, which applies a unigram
popularity model in some cases, to filter the training data for an
n-gram model (so it won't be able to make n-gram decisions about thsoe
words).
Kenneth
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