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#X text 176 446 is signal power and "m" is mask.;
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#X text 175 464 (zero if s < m).;
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#X text 483 212 number of;
#X text 491 227 frames;
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#X obj 480 113 r window-msec;
#X obj 481 136 / 4;
#X text 521 133 hop size (analysis;
#X text 546 149 period) in msec;
#X obj 359 408 tabreceive~ \$0-mask;
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#X obj 371 218 <;
#X obj 235 258 expr 1/($f1+1);
#X text 134 17 calculate a mask using N msec of background noise;
#X text 43 354 current power (for each channel);
#X text 367 430 average the current power into the last mask to get
the new mask. The new value is weighted 1/n on the nth iteration.;
#X text 390 312 weight to average in new power to mask;
#X text 11 203 loop counting to desired;
#X text 78 219 number of frames;
#X text 72 39 This loops for "make-mask" milliseconds \, averaging
power in each channel over that amount of time. This is done by a moving
average whose weight is adjusted to average each new value equally
with each of the accumulating ones.;
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#X restore 132 203 pd calculate-mask;
#X text 91 98 real Fourier transform;
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#X msg 357 80 \; pd dsp 1 \; window-size 1024;
#X text 193 355 ... but not less than zero;
#X text 101 561 real inverse Fourier transform;
#X text 196 498 normalize by 2/(3N) where N is window size;
#X text 168 332 current power ("s") minus level-adjusted mask ("m")
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#X text 156 175 compute power (call it "s") in each channel;
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#X text 203 395 protect against division by zero;
#X text 179 426 compute sqrt((s-m)/s) where "s";
#X text 296 204 <- subwindow calculates noise mask;
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#X restore 94 423 pd fft-analysis;
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#X text 56 20 calculate Hann window table (variable window size) and
constants window-hz (fundamental frequency of analysis) \, window-sec
and window-msec (analysis window size in seconds and msec)., f 56
;
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#X text 184 335 noise;
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#X text 159 304 read a sample;
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#X msg 65 212 read -resize \$1 \$2;
#X msg 79 327 \; read-sample ../sound/bell.aiff;
#X msg 77 374 \; read-sample ../sound/voice.wav;
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#X restore 354 445 pd insample;
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#X text 315 320 off;
#X text 270 303 masking;
#X text 107 12 DENOISER;
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#X text 232 235 sample duration \, msec;
#X text 95 71 looped sample playback;
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#X text 243 315 filtered noise;
#X text 56 20 TEST SIGNAL: looped sample plus noise. The inlets control
amplitude of each in dB., f 42;
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#X restore 94 388 pd test-signal;
#X text 82 332 sampler;
#X text 391 325 calculate noise mask, f 10;
#X obj 94 460 output~;
#X msg 387 360 \; make-mask 2000;
#X msg 269 342 15;
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#X text 28 35 This table (1002-mask) is the average power measured
in each channel of the spectrum \, presumed to represent the noise
floor.;
#X restore 354 489 pd mask-table;
#X text 99 301 amplitudes (dB);
#X text 50 47 This patch attempts to scrub the noise floor from a sample
in two steps. First using the "make-mask" message (which is caught
in the "fft-analysis" window) \, you estimate the background spectrum.
You would normally do this at a moment when only the background noise
is audible. Then \, turn on "masking" (to 15 by default \, but try
other values) and the patch will try to clean the background noise
out of a signal., f 65;
#X text 50 153 For this demonstration \, you control the amplitudes
of a looping sample and a filtered noise source. Normally you'd hit
"calculate noise mask" with only the noise turned on \, then turn both
the noise and the sampler on \, and also "masking" \, to see if the
patch can clean the noise out of the signal. Open the "fft-analysis"
window to see the algorithm \, or the "insample" window to change samples
\, or "mask-table" to see the current mask (the average signal power
of the noise to clean out of the signal)., f 65;
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