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/************************************************************************/
/* */
/* Centre for Speech Technology Research */
/* University of Edinburgh, UK */
/* Copyright (c) 1996,1997 */
/* All Rights Reserved. */
/* */
/* Permission is hereby granted, free of charge, to use and distribute */
/* this software and its documentation without restriction, including */
/* without limitation the rights to use, copy, modify, merge, publish, */
/* distribute, sublicense, and/or sell copies of this work, and to */
/* permit persons to whom this work is furnished to do so, subject to */
/* the following conditions: */
/* 1. The code must retain the above copyright notice, this list of */
/* conditions and the following disclaimer. */
/* 2. Any modifications must be clearly marked as such. */
/* 3. Original authors' names are not deleted. */
/* 4. The authors' names are not used to endorse or promote products */
/* derived from this software without specific prior written */
/* permission. */
/* */
/* THE UNIVERSITY OF EDINBURGH AND THE CONTRIBUTORS TO THIS WORK */
/* DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING */
/* ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT */
/* SHALL THE UNIVERSITY OF EDINBURGH NOR THE CONTRIBUTORS BE LIABLE */
/* FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES */
/* WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN */
/* AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, */
/* ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF */
/* THIS SOFTWARE. */
/* */
/************************************************************************/
/* Author: Richard Caley (rjc@cstr.ed.ac.uk) */
/* Date: Tue May 27 1997 */
/************************************************************************/
/************************************************************************/
/* */
/* temporary place fro some new functions. */
/* */
/************************************************************************/
#include <cmath>
#include <cstdlib>
#include "EST_Wave.h"
#include "EST_wave_aux.h"
#include "EST_simplestats.h"
#include "EST_cutils.h"
EST_Wave difference(EST_Wave &a, EST_Wave &b)
{
int i, j;
int size = Lof(a.num_samples(), b.num_samples());
EST_Wave diff = a;
// ERROR REORG - this needs to return a proper error
if (a.num_channels() != b.num_channels())
{
cerr << "Error: Can't compare " << a.num_channels() <<
" channel EST_Wave with " << b.num_channels() << " channel EST_Wave\n";
return diff;
}
for (i = 0; i < size; ++i)
for (j = 0; j < a.num_channels(); ++j)
diff.a(i, j) = a.a(i, j) - b.a(i, j);
return diff;
}
void meansd(EST_Wave &tr, float &mean, float &sd, int channel)
{
float var=0.0;
int i, n;
for (n = 0, i = 0, mean = 0.0; i < tr.num_samples(); ++i)
{
mean += tr.a(i, channel);
++n;
}
mean /= n;
for (i = 0, mean = 0.0; i < tr.num_samples(); ++i)
var += pow(tr.a(i, channel) - mean, float(2.0));
var /= n;
sd = sqrt(var);
}
float rms_error(EST_Wave &a, EST_Wave &b, int channel)
{
int i;
int size = Lof(a.num_samples(), b.num_samples());
float sum = 0;
for (i = 0; i < size; ++i)
sum += pow(float(a.a(i, channel) - b.a(i, channel)), float(2.0));
sum = sqrt(sum / size);
return sum;
}
float abs_error(EST_Wave &a, EST_Wave &b, int channel)
{
int i;
int size = Lof(a.num_samples(), b.num_samples());
float sum = 0;
for (i = 0; i < size; ++i)
{
// cout << i << " " << a.a(i, channel) << " " << b.a(i, channel) << endl;
sum += fabs(float(a.a(i, channel) - b.a(i, channel)));
}
return sum / size;
}
float correlation(EST_Wave &a, EST_Wave &b, int channel)
{
int i;
int size = Lof(a.num_samples(), b.num_samples());
float predict,real;
EST_SuffStats x,y,xx,yy,xy,se,e;
float cor,error;
for (i = 0; i < size; ++i)
{
// cout << a.a(i, channel) << " " << b.a(i, channel) << endl;
predict = b.a(i, channel);
real = a.a(i, channel);
x += predict;
y += real;
error = predict-real;
se += error*error;
e += fabs(error);
xx += predict*predict;
yy += real*real;
xy += predict*real;
}
cor = (xy.mean() - (x.mean()*y.mean()))/
(sqrt(xx.mean()-(x.mean()*x.mean())) *
sqrt(yy.mean()-(y.mean()*y.mean())));
// cout << xy.mean() << " " << x.mean() << " " << y.mean() << " " << xx.mean() << " " << yy.mean() << endl;
// cout << "RMSE " << sqrt(se.mean()) << " Correlation is " << cor << " Mean (abs) Error " << e.mean() << " (" << e.stddev() << ")" << endl;
return cor;
}
void absolute(EST_Wave &wave)
{
int i, j;
for (i = 0; i < wave.num_samples(); ++i)
for (j = 0; j < wave.num_channels(); ++j)
wave.a(i, j) = abs(wave.a(i, j));
}
EST_FVector rms_error(EST_Wave &a, EST_Wave &b)
{
int i;
EST_FVector e;
// ERROR REORG - this needs to return a proper error
if (a.num_channels() != b.num_channels())
{
cerr << "Error: Can't compare " << a.num_channels() <<
" channel EST_Wave with " << b.num_channels() << " channel EST_Wave\n";
return e;
}
e.resize(a.num_channels());
for (i = 0; i < a.num_channels(); ++i)
e[i] = rms_error(a, b, i);
return e;
}
EST_FVector abs_error(EST_Wave &a, EST_Wave &b)
{
int i;
EST_FVector e;
// ERROR REORG - this needs to return a proper error
if (a.num_channels() != b.num_channels())
{
cerr << "Error: Can't compare " << a.num_channels() <<
" channel EST_Wave with " << b.num_channels() << " channel EST_Wave\n";
return e;
}
e.resize(a.num_channels());
for (i = 0; i < a.num_channels(); ++i)
e[i] = abs_error(a, b, i);
return e;
}
EST_FVector correlation(EST_Wave &a, EST_Wave &b)
{
int i;
EST_FVector cor;
// ERROR REORG - this needs to return a proper error
if (a.num_channels() != b.num_channels())
{
cerr << "Error: Can't compare " << a.num_channels() <<
" channel EST_Wave with " << b.num_channels() << " channel EST_Wave\n";
return cor;
}
cor.resize(a.num_channels());
for (i = 0; i < a.num_channels(); ++i)
cor[i] = correlation(a, b, i);
return cor;
}
EST_Wave error(EST_Wave &ref, EST_Wave &test, int relax)
{
int i, j, k, l;
EST_Wave diff;
diff = ref;
int t;
// relaxation allows an error to be ignored near boundaries. The
// degree of relation specifies how many samples can be ignored.
int *r = new int[relax*3];
for (l = 0; l < ref.num_channels(); ++l)
for (i = 0; i < ref.num_samples(); ++i)
{
t = 0;
for (k = 0, j = Gof((i - relax), 0); j < i + relax + 1; ++j, ++k)
{
if (ref.a(i, l) > 0.5)
r[k] = ((j < test.num_samples()) && (test.a(j, l)> 0.6)) ?1
: 0;
else
r[k] = ((j < test.num_samples()) && (test.a(j, l)< 0.4)) ?1
: 0;
t |= r[k];
}
diff.a(i, l) = t;
}
delete [] r;
return diff;
}
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