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    <p>You can use the <a href="http://en.wikipedia.org/wiki/Fast_Fourier_transform" rel="noreferrer">Fourier Transform</a> to calculate the frequency spectrum from an audio sample. From this output, you can use the <a href="http://en.wikipedia.org/wiki/Pitch_%28music%29" rel="noreferrer">frequency values for particular notes</a> to turn this into a list of notes heard during the sample. Choosing the strongest notes heard per sample over a series of samples should give you a decent map of the different notes used, which you can compare to the different <a href="http://en.wikipedia.org/wiki/Music_scale" rel="noreferrer">musical scales</a> to get a list of the possible scales that contain that combination of notes.</p> <p>To help decide which particular scale is being used, make a note (no pun intended) of the most frequently heard notes. In Western music, the root of the scale is typically the most common note heard, followed by the fifth, and then the fourth. You can also look for patterns such as common <a href="http://en.wikipedia.org/wiki/Chord_%28music%29" rel="noreferrer">chords</a>, <a href="http://en.wikipedia.org/wiki/Arpeggio" rel="noreferrer">arpeggios</a>, or <a href="http://en.wikipedia.org/wiki/Chord_progression" rel="noreferrer">progressions</a>.</p> <p>Sample size will probably be important here. Ideally, each sample will be a single note (so that you don't get two chords in one sample). If you <a href="http://en.wikipedia.org/wiki/Low_pass_filter" rel="noreferrer">filter</a> out and concentrate on the low frequencies, you may be able to use the volume spikes ("clicks") normally associated with percussion instruments in order to determine the song's tempo and "lock" your algorithm to the beat of the music. Start with samples that are a half-beat in length and adjust from there. Be prepared to throw out some samples that don't have a lot of useful data (such as a sample taken in the middle of a slide).</p>
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    1. POAlgorithms for determining the key of an audio sample
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    1. COIt's not that easy to extract pitch from a power spectrum - there are much better pitch detection algorithms.
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    2. COThe whole process is a complex one. But very interesting. Chords I think create much complexity as they generate their own resonance and harmonic frequency that must be very difficult to account for in an algorith!
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    3. CO@AlexW- Yes harmonic resonance is present, but it appears at a much lower magnitude than the chord itself. If you know the chord, you can predict the harmonics that might be heard and filter them out of your results accordingly.
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