This week, I explored CART models a little bit, but couldn't complete it. The models are trained using wagon in speech tools with the following contextual information:
Current phone, previous phone, next phone, syllable postion, phonological features, phone type etc.,
Complete list of features are listed in the below URL:
Once the training is completed, the output is built in a tree which is given as input along with testing data to wagon_test in speech tools and there by it predicts the duration of the each phone using the contextual information using tree structure.
Regarding replacing of traditional MFCC features either with PNCC or phonological features, I need to compute acoustic models for WSJ database replacing these features instead of MFCC. It's in process, and once acoustic models are built, the rest of the testing process is same.
Work to do:
By next week, I would be able to complete one of these two and the next one thereafter. In the final week, I upload all codes to svn and integrate these new techniques with the current working pronunciation evaluation model @ http://talknicer.net/~ronanki/