delta.cc

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/*                Centre for Speech Technology Research                  */
/*                     University of Edinburgh, UK                       */
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/*************************************************************************/
/*                     Author :  Simon King                              */
/*                     Date   :  July 1995                               */
/*-----------------------------------------------------------------------*/
/*                 Compute delta coefficients for                        */
/*                        Tracks and Tracks                              */
/*                                                                       */
/*=======================================================================*/
#include <cstdlib>
#include "EST_Track.h"
#include "EST_Wave.h"

using namespace std;

# define MAX_DELTA_ORDER 2
/// max. number of points on which the delta co-eff is based
# define MAX_REGRESSION_LENGTH 4

static float compute_gradient(const EST_FVector &x, int num_points);

void delta(EST_Track &tr, EST_Track &d, int regression_length)
{
    ssize_t reg_index, this_index;
    
    // need at least two points to compute gradient
    if ((regression_length < 2)||(regression_length > MAX_REGRESSION_LENGTH)){
    cerr << "delta(EST_Track&, int) : ERROR : regression_length is "
        << regression_length << endl;
    exit(0);
    }
    
    // temp stores the points passed to compute_gradient
    EST_FVector temp(regression_length);
    
    for (ssize_t j = 0; j < tr.num_channels(); j++ )
    for (ssize_t i = 0; i < tr.num_frames(); i++)
    {
        // copy values needed to compute gradient into temp[]
        for (reg_index=0; reg_index<regression_length; reg_index++)
        {
        // gradient is computed from points to left of current time
        // rather than points centred around the current time
        this_index = i - reg_index;
        if (this_index >= 0)
            temp[reg_index] = tr.a(this_index, j);
        }
        
        // gradient at frame 0 is defined as 0
        if (i < 1)
        d.a(i, j) = 0.0;
        else if (i < regression_length - 1)
        // enough data, but would prefer more
        // number of points available is only i+1
        d.a(i, j) = compute_gradient(temp, i + 1);
        else
        // plenty of data, use the last regression_length points
        d.a(i, j) = compute_gradient(temp, regression_length);
    }
}

void delta(EST_Wave &tr, EST_Wave &d, int regression_length)
{
    int reg_index, this_index;
    
    // need at least two points to compute gradient
    if ((regression_length < 2)||(regression_length > MAX_REGRESSION_LENGTH)){
    cerr << "delta(EST_Track&, int) : ERROR : regression_length is "
        << regression_length << endl;
    exit(0);
    }
    
    // temp stores the points passed to compute_gradient
    EST_FVector temp(regression_length);
    
    for (int j = 0; j < tr.num_channels(); j++ )
    for (int i = 0; i < tr.num_samples(); i++)
    {
        // copy values needed to compute gradient into temp[]
        for (reg_index=0; reg_index<regression_length; reg_index++)
        {
        // gradient is computed from points to left of current time
        // rather than points centred around the current time
        this_index = i - reg_index;
        if (this_index >= 0)
            temp.a_no_check(reg_index) = (float)tr.a(this_index, j);
        }
        
        // gradient at frame 0 is defined as 0
        if (i < 1)
        d.a(i, j) = 0;
        else if (i < regression_length - 1)
        // enough data, but would prefer more
        // number of points available is only i+1
        d.a(i, j) = (short)compute_gradient(temp, i + 1);
        else
        // plenty of data, use the last regression_length points
        d.a(i, j) = (short)compute_gradient(temp, regression_length);
    }
}

static float compute_gradient(const EST_FVector &x, int num_points)
{
    float gradient;
    
    // NB x[0] is the point LATEST in time
    // so x[1] is really x[t-1]
    
    // time between points is assumed to be one unit
    
    // These are solutions to least-squares fit of straight line
    // to num_points points.
    switch (num_points){
    
    case 1:
    gradient = 0.0;
    break;
    
    case 2:
    gradient = x(0) - x(1);
    break;
    
    case 3:
    gradient = (x(0) -x(2)) / 2.0;
    break;
    
    case 4:
    gradient = ( (3.0*x(0)) + x(1) - x(2) - (3.0 * x(3)) ) / 10.0;
    break;
    
    default:
    
    cerr << "compute_gradient(float*, int) : ERROR : num_points is" 
        << num_points << endl;
    
    exit(0);
    break;
    }
    
    return gradient;
}