Philipp (and others), I'm wondering what people's experience is regarding when truecasing is applied.
One option is to truecase the training data, then train your TM and LM using that truecased data. Another option would be to lowercase the data, train TM and LM on the lowercased data, and then perform truecasing after decoding. I assume that the former gives better results, but the latter approach has an advantage in terms of extensibility (namely if you get more data and update your truecase model, you don't have to re-train all of your TMs and LMs). Does anyone have any insights they would care to share on this? Thanks, Lane
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