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.
>
>
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