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Sorry, such functionality is not built into SRILM, and would have to
be built on top of it by querying various probability models that
incorporate the co-occurance of words. Personally I don't
experience with this type of application but someone else on the
list might.<br>
<br>
Andreas<br>
<br>
<br>
On 2/2/2012 7:24 AM, John Day wrote:
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cite="mid:1328196256.12588.YahooMailNeo@web114411.mail.gq1.yahoo.com"
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<div style="color:#000; background-color:#fff; font-family:arial,
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<div>Hi Andreas,</div>
<div> Can you (or the group) tell me if srilm could be used to
query language models in such a way as to 'narrow down' the
search for a "partially known word" where the context of its
usage is known. By "partially known" I mean hints such as word
prefixes or endings are known. The "context of usage" is
equivalent, I think, to stating that the likelihood of the
hidden word is increased if it is preceded or followed by a
given set of words associated with some topic. <br>
</div>
<div><br>
</div>
<div>So I would like to 'leverage' srilm and language model
queries by using topic models to suggest some words associated
with a certain topic.</div>
<div><br>
</div>
<div>For example, find the most likely words, that begin with
"st", given a "context set" (suggested by some 'sociology'
topic model) containing the words "neighborhood, behavior,
customs, environment".</div>
<div><br>
</div>
<div>Does that make sense? Do you think srilm could be used to
execute a query like that?</div>
<div><br>
</div>
<div>Thanks,</div>
<div>John Day</div>
<div>Palm Bay, Florida</div>
</div>
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