6. Part 4: Try to beat the MFCC front end (Optional)

In this optional exercise, you have the opportunity to improve on your MFCC front end. To get started, type the commands:
mkdir -p ~/e6884/lab1ec/
cd ~/e6884/lab1ec/
cp ~stanchen/e6884/lab1/.mk_chain .
Copy over your Lab1_FE.C from Part 1, and also Lab1_DTW.H from Part 2 if you have one and like it. If you want to add additional parameters to your front end and have figured out how to do this, then you can also grab a copy of Lab1_FE.H from ~stanchen/e6884/lab1/.

For this exercise, you will need to compile DcdDTW like so:
smk DcdDTW
We have provided two development sets for optimizing your front ends, a mini-test set consisting of ~100 utterances and a larger test set consisting of ~1000 utterances. To run the DcdDTW in the current directory on these test sets, run
lab1p4small.sh
lab1p4large.sh
for the small and large test sets, respectively. These scripts are set up to use the full MFCC pipeline (windowing + FFT + melbin w/ log + DCT), and you can change what signal processing is done by modifying the modules you developed in Part 1 of the lab. If the algorithms you would like to implement cannot be realized within this framework (e.g., you don't want to do an FFT), please contact one of the professors and we can tell you how to do this.

The task is set up to be speaker-independent: the speaker used to provide the templates for a test set may have no relation to the speaker of that test set.

The evaluation test set we will use to determine which front end wins the “Best Front End” award will not be released until after this assignment is due, to prevent the temptation of developing techniques that may only work well on the development test sets. This is consistent with the evaluation paradigm used in government-sponsored speech recognition competitions, the primary ones being the [NIST Spoken Language Technology Evaluations].