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I think I found the source of the problem. I used weight as an NSNumber=1.5 in the test. After reading your post/doc again I change it back to nil. Since then the CPU utilization has become a lot better. I also regenerate both language model but I suspect this is not the problem. Both corpus files are in the VocabularyFiles folder with .txt extension.
I was using weight=1.5 because the framework picks up too many out of vocabulary words with weight=nil. I was hoping increasing weight will make rejecto more effective but it seems to cause high CPU problem.
I am still struggling with __REJ (rejected words) being delivered in hypothesis. The function:
[languageModelGenerator deliverRejectedSpeechInHypotheses: (BOOL)FALSE];
seems to have no effect in my test setup (I tried using both TRUE or FALSE).