Ok, you produce an FFT, from this you grab the fundamental frequency, and a sufficient number of harmonics. With this, you can compare it to another FFT result ( one that was previously calculated to be true. So, you record yourself saying "a", and take the FFT of that ). Since everytime you say the vowel will be different, a direct equals operation will not work, as there will be descrepencies in what is found. So, you want to have a threshold, and use fuzzy logic and decide what is the most likely thing it could be. What I'd look at is the spacing and number of harmonics found. The fundamental frequency I can't see being too important ( say, for instance, you got a girl to say something, it'd be a higher pitch, but the spacing of the harmonics, and the number of them will probably still be the same ). Of course, something like this would break instantly with a different accent. But hey, I don't write speech recognition stuff, I just did/am doing DSP in my degree.

You have to remember that you're unique, just like everybody else.

[edited by - python_regious on April 18, 2004 6:39:01 PM]