First of forgive me if this is the wrong place to post about this but I am relatively new to the forum.

For the past 3 weeks I have been working on a voice recognition library. Its come to a stage where it can be used more or less to detect words from a small vocabulary set (about say 10). It is not perfect yet but can differentiate between left,right, up and down.

WARNING! COMPLEX MATH TALK AHEAD:

The library also contains techniques to recognize phonemes. The way it works is simple, 4 bandpass filters are created, from each of these filters the power is collected using an absolute summation or absolute integral. Then the amount the complexity of the signal in each of these filters is determined using an absolute differential divided by an absolute integral. After this to generate “fingerprint” I get the absolute integral of filter[n]-mean/variance of the powers and the same for the complexity. This produces a 5x2 matrix which is compared against a model matrix.

End of math talk

Code is on github as I stated there is very less (no) documentation yet and I have to work on training samples.

I have not included my training samples yet in the github repo but they should be up. http://arjo129.github.com/uSpeech/