Basically, (I know I've asked a simular question, but I have been away and really thought about it this time)!
Let me try and explain this in the best way possible:
Basically, I'm attempting to create an algorithm that takes a voice sample (.wav) of someone saying either "Yes", or "No". Now, in order to do this I am attempting to split the sample into equal blocks in order to get the Phones.
Now, I have thought about this..
I don't need to technically analise all of Phones, I can identify if the the sample is either "Yes" or "No" by just looking for a "Y" Phone. Because if a "Y" doesn't exist then the sample is "No". So, I can handle this by implementing a decision tree.
Ok, so to my question. I know that this can be achieved using Zero-Crossing, but, I don't have any experience in this (Ok, people are going to tell me to stop doing it then) but, we all had to learn somewhere, right?
If someone could possibly link me to a website or a book where I can learn about the Zero-crossing method? Then it would be great.
The main thing I don't understand about it is, how can Zero-crossing determine whether the Phone is a "Y"? Or, will I need to have some samples of "Y" in order to match through Correlation?, or something.
I hope someone can advise me.