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I am using SRI to produce some reverse language models and are quite big.<br>Stats: training data: 1.1G words<br> 88M sentences<br><br>but system was limited to 39k words (wordlist.txt) by:<br>ngram-count -memuse -order 3 -interpolate -kndiscount -unk -vocab ../lang-data/wordlist.txt -limit-vocab -text ../lang-data/${training}-${reverse}.xml -lm ${training}-reverse-lm${trigram}<br><br><br>Is there other options to reduce LM size since trigrams are 1.7G? (without so much lost in performance)?<br><br>Thanks,<br><br><br>Luis<br><br> </body>
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