Factored LMs and interpolated models

[Kevin Duh]

There is no easy way to interpolate word and class ngram models in the 
factored language model framework. Factor language models support only 
interpolation of an N-gram probability estimate and its corresponding 
lower-order estimate, which is similar to the "interpolate" option in 
"ngram-count."

You could conceivably treat the word and the class as your factors and 
perform interpolation whenever you back off from one set of these 
conditioning variables to a subset. However, this backoff nature makes 
the interpolation different from the traditional interpolation of 
parallel n-grams. Probably the best thing to do is to use the usual 
SRILM tools for this.

Hope this helps,
Kevin Duh

Tanel Alumäe wrote:

>Hello,
>
>I'm experimenting with factored language modeling implementation in
>SRILM. I got some nice results and now want to compare them with the
>traditional approach where a word-trigram LM is interpolated with the
>parallel class trigram. Is it possible to create a factored LM that
>actually implements such traditional interpolation? 
>
>Thanks in advance,
>Tanel A.
>  
>