I have been reading up on FFT and Pitch Detection for a while now, but I\'m having trouble piecing it all together.
I have worked out that the Accelerate framework is pr
Frequency and pitch are not the same thing - frequency is a physical quantity, pitch is a psychological percept - they are similar, but there are important differences, which may or may not matter to you, depending on the type of instrument for which you are trying to measure pitch.
You need to read up a little on the various pitch detection algorithms (and on the meaning of pitch itself), decide what algorithm you want to use and only then set about implementing it. See this Wikipedia page for a good overview of pitch and pitch detection (note that you can use FFT for the autocorrelation-based and frequency domain methods).
As for using the FFT to identify peaks in a spectrum and their associated frequencies, there are many questions and answers related to this on SO already, see for example: How do I obtain the frequencies of each value in an FFT?
I have an example implementation of an Autocorrelation function available online for ios 5.1. Look at this post for a link to the implementation AND functions on how to find the nearest note and how to create a string representing the pitch (A, A#, B, B#, etc...)
While the FFT is very useful in many applications, it might not be the most accurate if you're trying to do simple pitch detection. (It can be as accurate, but you have to deal with complex numbers to do a lot of phase calculations)