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1852980
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2009-12-05T18:19:08.813
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2009-12-05T23:59:30.893
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text
Body
You're looking for a <a href="http://en.wikipedia.org/wiki/Frequency_estimation" rel="noreferrer">frequency estimation</a> or <a href="http://en.wikipedia.org/wiki/Pitch_detection_algorithm" rel="noreferrer">pitch-detection</a> algorithm. Most people suggest finding the maximum value of the FFT, but this is overly simplistic and doesn't work as well as you might think. If the <a href="http://en.wikipedia.org/wiki/Missing_fundamental" rel="noreferrer">fundamental is missing</a> (a timpani, for instance), or one of the harmonics is larger than the fundamental (a trumpet, for instance), it won't detect the correct frequency. Trumpet spectrum: <a href="http://www.eng.cam.ac.uk/DesignOffice/mdp/electric_web/AC/02284.jpg" rel="noreferrer">Trumpet spectrum http://www.eng.cam.ac.uk/DesignOffice/mdp/electric_web/AC/02284.jpg</a> Also, you're wasting processor cycles calculating the FFT if you're only looking for a specific frequency. You can use things like the <a href="http://www.embedded.com/story/OEG20020819S0057" rel="noreferrer">Goertzel algorithm</a> to find tones in a specific frequency band more efficiently. You really need to find "the first significant frequency" or "the first frequency with strong harmonic components", which is more ambiguous than just finding the maximum. <a href="http://en.wikipedia.org/wiki/Autocorrelation" rel="noreferrer">Autocorrelation</a> or the <a href="http://cnx.org/content/m11714/latest/" rel="noreferrer">harmonic product spectrum</a> is better at finding the true fundamental for real instruments, but if the instrument is <a href="http://en.wikipedia.org/wiki/Inharmonicity" rel="noreferrer">inharmonic</a> (most are), then the wave shape is changing over time, and I suspect it won't work as well if you try to measure more than a few cycles at a time, which decreases your accuracy.
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1. PO.NET Library to Identify Pitches
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1. USendolith
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