Onsets Onset detector

Onsets.kr(chain, threshold, odftype)

An onset detector for musical audio signals - detects the beginning of notes/drumbeats/etc. Outputs a control-rate trigger signal which is 1 when an onset is detected, and 0 otherwise.

chain - an FFT chain

threshold - the detection threshold, typically between 0 and 1, although in rare cases you may find values outside this range useful

odftype - the function used to analyse the signal (options described below; OK to leave this at its default value)

For the FFT chain, you should typically use a frame size of 512 or 1024 (at 44.1 kHz sampling rate) and 50% hop size (which is the default setting in SC). For different sampling rates choose an FFT size to cover a similar time-span (around 10 to 20 ms).

The onset detection should work well for a general range of monophonic and polyphonic audio signals. The onset detection is purely based on signal analysis and does not make use of any "top-down" inferences such as tempo.

Example

(

s.boot.doWhenBooted {

// Prepare the buffers

b = Buffer.alloc(s, 512);

// Feel free to load a more interesting clip!

// a11wlk01 is not an ideal example of musical onsets.

d = Buffer.read(s, "sounds/a11wlk01.wav");

};

)

////////////////////////////////////////////////////////////////////////////////////////////////

// Move the mouse to vary the threshold

(

x = {

var sig, chain, onsets, pips;

// A simple generative signal

sig = LPF.ar(Pulse.ar(TIRand.kr(63,75,Impulse.kr(2)).midicps), LFNoise2.kr(0.5).exprange(100, 10000)) * Saw.ar(2).range(0, 1);

// or, uncomment this line if you want to play the buffer in

//sig = PlayBuf.ar(1, d, BufRateScale.kr(d), loop: 1);

chain = FFT(b, sig);

onsets = Onsets.kr(chain, MouseX.kr(0,1), \rcomplex);

// You'll hear percussive "ticks" whenever an onset is detected

pips = WhiteNoise.ar(EnvGen.kr(Env.perc(0.001, 0.1, 0.2), onsets));

Out.ar(0, Pan2.ar(sig, -0.75, 0.2) + Pan2.ar(pips, 0.75, 1));

}.play;

)

x.free; // Free the synth

////////////////////////////////////////////////////////////////////////////////////////////////

// Or we could expand this multichannel, run a series of different thresholds at the same time,

// to sonify the effect of the threshold value.

// A little hard to listen to at first: try and identify a pitch at which the best sort of

// detection is happening.

// You'll hear "bobbling" at low pitches where the threshold is definitely too low.

(

var threshes = (0.1, 0.2 .. 1);

x = {

var sig, chain, onsets, pips;

// A simple generative signal

sig = LPF.ar(Pulse.ar(TIRand.kr(63,75,Impulse.kr(2)).midicps), LFNoise2.kr(0.5).exprange(100, 10000)) * Saw.ar(2).range(0, 1);

// or, uncomment this line if you want to play the buffer in

//sig = PlayBuf.ar(1, d, BufRateScale.kr(d), loop: 1);

chain = FFT(b, sig);

onsets = Onsets.kr(chain, threshes, \rcomplex);

// Generate pips at a variety of pitches

pips = SinOsc.ar((threshes).linexp(0, 1, 440, 3520), 0, EnvGen.kr(Env.perc(0.001, 0.1, 0.5), onsets)).mean;

Out.ar(0, Pan2.ar(sig, -0.75, 0.2) + Pan2.ar(pips, 0.75, 1));

}.play;

)

x.free; // Free the synth

[b,d].do(_.free); // Free the buffers

The type argument chooses which onset detection function is used. In many cases the default will be fine. The following choices are available:

- \power - generally OK, good for percussive input, and also very efficient
- \magsum - generally OK, good for percussive input, and also very efficient
- \complex - performs generally very well, but more CPU-intensive
- \rcomplex - performs generally very well, and slightly more efficient than \complex
- \phase - generally good, especially for tonal input, medium efficiency
- \wphase - generally very good, especially for tonal input, medium efficiency
- \mkl - generally very good, medium efficiency, pretty different from the other methods

Which of these should you choose? The differences aren't large, so I'd recommend you stick with the default \rcomplex unless you find specific problems with it. Then maybe try \wphase. The \mkl type is a bit different from the others so maybe try that too. They all have slightly different characteristics, and in tests perform at a similar quality level.

For more details of all the processes involved, the different onset detection functions, and their evaluation, see

D. Stowell and M. D. Plumbley. Adaptive whitening for improved real-time audio onset detection. Proceedings of the International Computer Music Conference (ICMC’07), Copenhagen, Denmark, August 2007.

Advanced features

Further options are available, which you are welcome to explore if you want. They are numbers that modulate the behaviour of the onset detector:

- relaxtime and floor are parameters to the whitening process used, a kind of normalisation of the FFT signal. (Note: in \mkl mode these are not used.)

- relaxtime specifies the time (in seconds) for the normalisation to "forget" about a recent onset. If you find too much re-triggering (e.g. as a note dies away unevenly) then you might wish to increase this value.
- floor is a lower limit, connected to the idea of how quiet the sound is expected to get without becoming indistinguishable from noise. For some cleanly-recorded classical music with wide dynamic variations, I found it helpful to go down as far as 0.000001.

- mingap specifies a minimum gap (in FFT frames) between onset detections, a brute-force way to prevent too many doubled detections.
- medianspan specifies the size (in FFT frames) of the median window used for smoothing the detection function before triggering.