I think that this approach should work rather well (I did very simillar project few years ago). Things you might consider: 1. You probably might want to use pre-emphasis filter on a signal. 2. In addition to MFCC features you can also include $\Delta$ and $\Delta\Delta$. Some theory can be found for example here: [click!][1] 3. Comparing against more templates in my case largely improved recognition rate. I think that the easiest way do so is by using k-NN algorithm on distances returned from DWT. Good luck! [1]: http://speechlab.eece.mu.edu/papers/Ye_thesis.pdf