I'm working on gender estimation from speech signal and I completed MFCC feature extraction. So now I'm trying to estimate gender from these features. But I have frames for an audio file and I extracted 13 coefficients for each frame. I'm thinking about using K Means algorithm for male or female classification but I not only have 1 vector. For example I have 250 frames and 13 coefficients for each frame. So I have a 250x13 array. How can I use K Means on an audio file which is divided in 250 frames? Should I classify each frame? I hope I can explain my question correctly. Thank you so much.
Male and female voices mainly differ on the fundamental frequency. The remaining frequencies, the formants, are specific to each phoneme and do not change a lot with gender. That is why you are able to recognize an "a" as an "a" independent of gender.
This said, I believe you could make a first approach trying to estimate fundamental frequency.
If you still want to use the MFCC then you can use all 250 frames for each person. You are working on a 13 dimension space where you can also form clusters.
For this purpose you can also use Gaussian Mixture Models (GMMs)