However, since FFTW works linearly, with a 256 element or 1024 element array only about 10% of the return array actually holds values up to about 5 kHz. These should be somewhat evenly distributed throughout the spectrum when interpreting them logarithmically. I am also applying a Hann function to each chunk of data to smooth out the window boundaries.įor example, I test using a mono audio file that plays tones at 120, 440, 1000, 5000, 1500 Hz. I have tried with window sizes of 256 up to 1024 bytes, and while the larger windows give more resolution in the low/mid range, it's still not that much. But with so little allocation to low/mid frequencies, I'm not sure how I can separate things cleanly to show the frequency distribution graphically. I understand that audio is logarithmic, and the FFT works with linear data.
Everything works, except the results from the FFT function only allocate a few array elements (bins) to the lower and mid frequencies. I run an FFT function on each buffer of PCM samples/frames fed to the audio hardware so I can see which frequencies are the most prevalent in the audio output. I am trying to build a graphical audio spectrum analyzer on Linux.
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