I’m implementing a ‘filter sweep’ effect (I don’t know if it’s called like that). What I do is basically create a low-pass filter and make it ‘move’ along a certain frequency range.
To calculate the filter cut-off frequency at a given moment I use a user-provided linear function, which yields values between 0 and 1.
My first attempt was to directly map the values returned by the linear function to the range of frequencies, as in cf = freqRange * lf(x). Although it worked ok it looked as if the sweep ran much faster when moving through low frequencies and then slowed down during its way to the high frequency zone. I’m not sure why is this but I guess it’s something to do with human hearing perceiving changes in frequency in a non-linear manner.
My next attempt was to move the filter’s cut-off frequency in a logarithmic way. It works much better now but I still feel that the filter doesn’t move at a constant perceived speed through the range of frequencies.
How should I divide the frequency space to obtain a constant perceived sweep speed?
Thanks in advance.
The frequency sweep effect you’re referring to is likely a wah-wah filter, named for the ubiquitous wah-wah pedal.
We hear frequency in terms of octaves, and sweeping through octaves with a logarithmic scale is the way to linearize it. Not to sound dismissive, but it sounds like what you’re doing is physically and mathematically correct. (You should spent as much time between 200 and 400 Hz as you do between 2000 and 4000 Hz, etc.) You just don’t like how it sounds. And that’s quite okay on both counts — audio is highly subjective.
To mix things up a bit, one option would be to try the Bark scale, which is based on psychoacoustics and the structure of the ear. As I understand it, this is designed to spend equal amounts of time in each of your ear’s internal “bandpass filters”.
You could always try a quadratic or cubic function between 0 and 1. Audio potentiometers often use a few piecewise quadratic or cubic sections to get their mapping.