2008/8/5 John D. Burger <[EMAIL PROTECTED]>:
> I'm starting to think it's a lost cause to try to get one LM
> implementation to act very much like the other.  Thanks for the
> insights, though!

I also spent some time unsuccessfully trying to exactly match the
SRILM toolkit's output. Aside from the various default settings, there
is some pruning going on when using kndiscount.
It's fairly easy to produce a LM that's within a few digits of
precision, but it's hard to replicate perfectly. Of course, those
pesky few last digits change the LM scores very much. You could just
re-tune, but that's non-deterministic so things are still not directly
comparable; kind of annoying.

There is also the larger question of "What does it get you?" (aside
from curiosity)... At the time, we were interested in building
monolithic SRI-style LMs on huge corpora. In the end, general interest
seems to have moved towards distributed LMs, mooting the original
exercise.
Um... Good luck!

~amittai
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