kuusama@news.funet.fi.tut.fi (Kuusama Juha) (10/01/90)
I'd like to see into audio data (50 kHz sampling rate) with qood resolution in frequency. While the normal Fourier methods give easily very good results in the high end of the spectrum, the low frequency resolution is very poor. (Audio data is presented with a logarithmic scale. For example 1024 point FFT gives frequency resolution of 24.4 Hz, which is more than 400 points in the top octave (10-20 kHz), put no point below 24 Hz, one point (!) in the lowest audio octave (20-40 Hz), etc.) The question: does anybody have a transform that gives the spectrum at user definable points, at points evenly spaced on logarithmic scale or something? I can use about everything adequately commented: a reference, Matlab function, C or Pascal code... Please mail or post your gems! -- Juha Kuusama, kuusama@korppi.tut.fi
cpenrose@sdcc13.ucsd.edu (Christopher Penrose) (10/02/90)
In article <1990Oct1.130615.5802@funet.fi> kuusama@news.funet.fi.tut.fi (Kuusama Juha) writes: >The question: does anybody have a transform that gives the spectrum at >user definable points, at points evenly spaced on logarithmic scale or >something? With a large enough table size, the phase vocoder can find the actual instantaneous frequencies of a signal (as averaged within the table size). Using a table size of 4096 or 8192 works fairly well for me. You can find a good phase vocoder in the book: Elements of Computer Music F. Richard "Dick" Moore Prentice-Hall
toma@hpsad.HP.COM (Tom Anderson) (10/09/90)
> I'd like to see into audio data (50 kHz sampling rate) with qood resolution > in frequency. While the normal Fourier methods give easily very good results > in the high end of the spectrum, the low frequency resolution is very poor. > (Audio data is presented with a logarithmic scale. For example 1024 point I asked a similar question a while back and got this excellent reply: Try looking at "An Algorithm and Architecture for Constant-Q Spectrum Analysis," by Gary W. Schwede. "Q" refers to the ratio of bandwidth to frequency, sometimes called the "quality" of a filter. Constant Q <==> logarithmic frequency. The paper is in the Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), April 1983, pp. 1384-1387. Tom Anderson toma@hpsad.hp.com "It's only hardware"