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\hypertarget{AudioMaskerExample.cc-example}{
\section{AudioMaskerExample.cc}
}
This is an example of how to use the \hyperlink{classAudioMasker}{AudioMasker} class See the example file to work out how to use these Audio masking classes
\begin{DoxyCodeInclude}
/*
*
* This example shows how to use Dr M.R. Flax's (2000) hybrid
* simultaneous audio masking class to find the masking threshold of a time domain
signal.
*
* The compilation of this file is demonstrated in Makefile.
* Run this file : ./AudioMaskerExample
* View the results of this file using www.octave.org by running the script view.m
* - simply type view once octave has started and you are in the suitable director
y.
*
* The input audio should be stored in the file INPUTFILENAME in text format - eac
h sample seperated by a * white space.
*
* ========================= HOWTO ===============================
* \code
* // First find the masking threshold
* AudioMasker masker(sampleFreq, count); // Create the audio masker class usi
ng fs=sampleFreq and count filters
* masker.excite(input, sampleCount); // find the mask for the array of input
data which has sampleCount time samples.
*
* // Now do something with the masking threshold ...
*
* // The frequency domain mask is now located here
* for (int j=0; j<count;j++)
* masker.mask[j]; // This is the mask at each of the count frequencies of
interest
*
* // A more sophisticated example - find the threshold for each Fourier bin
* double fact=(double)sampleFreq/((double)sampleCount-1.0); // convert from a
n index to the equivalent * Fourier bin frequency
* for (int j=0; j<halfSampleCount;j++){
* cout<<"finding for freq "<<j*fact<<'\t'; // The frequency we are inspec
ting
* double threshold=masker.findThreshold(j*fact); // The masking threshold
* 20*log10(threshold); // The threshold in decibels (dB)
* }
*
* \endcode
* // The following example calculates the spectral power and the masking thresh
old for each Fourier bin of interest ...
*/
#include <math.h>
#include "AudioMasker.H"
#define INPUTFILENAME "audio.44100.txt" // input file - text written samples sepe
rated by white spaces
#define POWFILENAME "fa.pow" // The power spectrum of the input signal
#define THRESHFILENAME "thresh.dat" // The masking threshold at each frequency of
the input signal
#define TMASKFILENAME "fa.t.mask" // The masking threshold for each filter CF
#define EXCITEFILENAME "fa.excite" // The excitation
#include <fstream>
int main(void){
// Setup many variables
// The number of time domain samples
int sampleCount=1024, halfSampleCount=(int)rint((double)sampleCount/2.0);
// The filter bank count and sample frequency
int count=50, sampleFreq=44100;
// The number of time domain samples to skip before the sample of interest.
int skip=8192-sampleCount-1;
// The input array to hold the input time data
double input[sampleCount];
// open the input file
ifstream inputF(INPUTFILENAME);
// Skip the first 2*'skip' samples.
int temp;
for (int i=0; i<skip;i++)
inputF >> temp >> input[0];
// load sampleCount samples as the input to the algorithm
for (int i=0; i<sampleCount;i++)
inputF >> input[i];
inputF.close();
ofstream outputCF("cf.dat"); // central freq. output file
ofstream outputT(TMASKFILENAME);
ofstream outputP(POWFILENAME); // Input data Fourier power file
// Get our masking function (class) ...
AudioMasker masker(sampleFreq, count);
//AudioMasker masker; // Can also be called like so with default filter banks a
nd sampleFrequency
masker.excite(input, sampleCount); // find the mask
for (int j=0; j<count;j++){ // Output the central freq to file
outputCF <<masker.pfb->cf[j]*((double)sampleCount/(double)sampleFreq)<<'\t';
outputT << 20*log10(masker.mask[j])<<'\t'; // output the mask for each filte
r CF to file
}
outputCF<<endl;
outputT<<endl;
realFFTData fftData(sampleCount); // Find the fourier transform for the output
of the power to file
realFFT fft(&fftData); // init the Fourier transform
for (int j=0; j<sampleCount;j++) // load the time domain input to the Fourier t
ransform
fftData.in[j]=input[j];
fft.fwdTransform(); // Perform the transformation of the time domain to the fre
quency domain.
fftData.compPowerSpec(); // Find the power spectrum
for (int j=0; j<sampleCount/2;j++) // Output the power spectrum to file
outputP<<20*log10(sqrt(fftData.power_spectrum[j]))<<'\t';
outputP<<endl;
outputCF.close();
outputT.close();
outputP.close();
ofstream outputF(THRESHFILENAME); // Find and output the masking threshold for
each Fourier bin in the power spectrum
double fact=(double)sampleFreq/((double)sampleCount-1.0); // convert from an in
dex to the equivalent Fourier bin frequency
for (int j=0; j<halfSampleCount;j++){
// cout<<"finding for freq "<<j*fact<<'\t';
outputF<<20*log10(masker.findThreshold(j*fact))<<'\t';
}
outputF<<endl;
outputF.close();
}
\end{DoxyCodeInclude}
|
