[PD] clap clap bonk bonk

[Hans Roels]

Hello,

I'm doing a hands clapping experiment and 'd like to use bonk~ to 
detect the beats. I need bonk~ to be a precise as possible to detect 
basic ryhtms (quarters, eights, semi-quavers, triolas).
The patch that I've made is working but I want to avoid any mistakes, 
I have set the number of frames to analyse, changed the minimum 
velocity and omitted durations faster than 100 ms.  Has anyone any 
other suggestions for improving this patch?

I'd like to be able to adjust the settings of bonk~ to the (spectral) 
features of the sound of clapping in your hands but the documentation 
in bonk-help about the learning mode is a bit incomplete I think. For 
example if I use the debounce message bonk~ stops outputting any 
values... The article from ICMC about fiddle and bonk is very 
interesting in general but very short about the specific operation 
mode of bonk.

The patch in attach writes/records the durations to an array, if you 
click on 'play' after recording these values are played using a 
simple sine with an amplitude envelope.

thanks,
Hans r  
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#X msg 540 348 print;
#X msg 537 132 mask 4 0.7;
#X text 632 114 Describes how energy in each frequency band masks later
energy in the band. Here the masking is total for 4 analysis periods
and then drops by 0.7 each period.;
#X text 582 280 Poll the current spectrum via "raw" outlet \, You can
set a very high threshold if you don't want attacks mixed in.;
#X msg 537 325 debug 0;
#X text 615 325 turn debugging on or off.;
#X text 614 196 Minimum "velocity" to output (quieter notes are ignored.)
;
#X text 634 29 Set low and high thresholds. Signal growth must exceed
the high one and then fall to the low one to make an attack. The unit
is the sum of the proportional growth in the 11 filter bands. Proportional
growth is essentially the logarithmic time derivative.;
#X msg 537 378 print 1;
#X text 605 380 print out filterbank settings;
#X text 9 32 The Bonk object takes an audio signal input and looks
for "attacks" defined as sharp changes in the spectral envelope of
the incoming sound. Optionally \, and less reliably \, you can have
Bonk check the attack against a collection of stored templates to try
to guess which of two or more instruments was hit. Bonk is described
theoretically in the 1998 ICMC proceedings \, reprinted on crca.ucsd.edu/~msp
.;
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#X text 155 133 Forget all templates and start learning new ones. The
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recommended.) Turn on the output volume above for audible feedback
as you train Bonk. "Learn 0" exits learn mode.;
#X text 155 217 Forget the last template. In Learn mode \, use "forget"
to erase and record over a template.;
#X text 220 253 Write templates to a file in text-editable format.
;
#X text 221 283 Read templates from a file.;
#X text 157 104 Minimum time (msec) between attacks in learn mode;
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#X text 5 284 In this patch \, after starting DSP \, you can print
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synthesizer output by raising its volume.;
#X text 8 144 Bonk's two outputs are the raw spectrum of the attack
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#X text 70 272 -npts 256;
#X text 44 244 default value:;
#X text 70 308 -hop 128;
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#X text 68 380 -halftones 6;
#X text 76 514 -overlap 1;
#X text 79 567 -firstbin 1;
#X text 71 454 -minbandwidth 1.5;
#X text 122 147 All frequency parameters are specified in 'bins'. One
bin is the sample rate divided by the window size. The minimum possible
bandwidth is 1.5 bins. Higher bandwidths give numerically more robust
outputs.;
#X text 43 229 Arguments and;
#X text 212 270 window size in points;
#X text 210 306 analysis period ("hop size") in points;
#X text 212 340 number of filters to use;
#X text 212 379 desired bandwidth of filters in halftones \, effective
in the exponentially spaced region. (At lower center frequencies the
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#X text 212 511 overlap factor between filters. If 1 \, the filters
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;
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#X text 212 567 center frequency \, in bins \, of the lowest filter.
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#X text 5 343 By default bonk's analysis is carried out on a 256-point
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