[SRILM User List] Why modified Kneser-Ney much slower than Good-Turing using make-big-lm?

Andreas Stolcke stolcke at icsi.berkeley.edu
Thu Aug 2 09:40:30 PDT 2012

On 8/2/2012 2:30 AM, Meng Chen wrote:
> Hi, I am training LM using *make-batch-counts*, *merge-batch-counts* 
> and *make-big-lm*. I compared the modified Kneser-Ney and Good-Turing 
> smoothing algorithm in *make-big-lm*, and found that the training 
> speed is much slower by modified Kneser-Ney. I checked the debug 
> information, and found that it run *make-kn-counts* and 
> *merge-batch-counts*, which cost most of the time. I wonder if the 
> extra two steps could run in *make-batch-counts*, so it could save 
> much time.
KN is slower because it has to first compute the regular ngram counts, 
then, in a second pass, make-kn-counts, which takes the merged ngram 
counts as input.  Because the counts have to be merged first (you are 
counting the ngram types, not the token frequencies) you need to do it 
in this order.


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