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On 3/5/2012 7:17 AM, Reham Al-Majed wrote:
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<font color="#333399"><font size="4">Hello ,, <br>
<br>
I've built class based n-gram by : <br>
<br>
1- define my classes<br>
2- use replace-words-with-classes<br>
3- use ngram-count to estimate the LM<br>
<br>
I want to use this class based n gram model with
disambig tool ,, The options (-factored and -count-lm)
interpret the LMs as factored and count based LMs ...
What about class-based ? How to tell disambig to
interpret the LM as a class-based ? <br>
<br>
I'm trying to use my class-based as an original n-gram
model, however the output for sample test seems
strange ... words in the test sample are always
disambiguated using the last word in the mapping file
!<br>
<br>
Actually I want the words be disambiguated using the
LM probabilities only without considering the
probabilities in the mapping file.. I use the options
-lmw 1 and -mapw 0 but the output still the same ... <br>
<br>
<br>
In short my questions are : <br>
<br>
1- Is it possible to use class-based n gram with
disabmig tool ? Or should I build my own
disambiguator using the output of ngram tool ?<br>
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<br>
Unfortunately disambig currently does not support the use of
class-based ngram LMs (what is implemented by ngram -classes).<br>
Two workarounds are <br>
1) if feasible, expand the class-ngram LM into a word-ngram LM
(using ngram -expand-classes).<br>
2) rewrite the class-ngram as a factored LM. This will require some
investment into understanding the much more general FLM mechanism.<br>
<br>
<br>
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2- How to make disambig tool use the probabilities of
LM ONLY ? <br>
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disambig -mapw 0 will do that.<br>
<br>
Andreas <br>
<br>
<br>
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