Revision 9e61900fad22c87341b4690c202c57f083eb1402 authored by mfederico on 04 August 2008, 13:06:52 UTC, committed by mfederico on 04 August 2008, 13:06:52 UTC
Now, the penalty for out-of-vocabulary words is specified 
by the parameter 

-lmodel-dub: dictionary upper bounds of language models

For instance, if you set it lmodel-dub to 1000000 (1M) and your actual 
vocabulary is let me say 200000 (200K), then the LM probabilty  of the
OOV word-class is divided by 800000 (800K), i.e. 1M-200K

You have to make sure that lmodel-dub is always larger than the LM 
dictionary.



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