void estimate_normalization_parameters(norm_info *channorm,
spect_dist_info **chandata, int dimen)
{
int ii, adjust;
ASSERT(channorm);
ASSERT(chandata);
ASSERT(dimen <= channorm->dim);
for (ii = 0; ii < dimen; ii++)
if (chandata[ii])
{
evaluate_parameters(chandata[ii]);
/* The additive expression is due to
** the normalization taking place before the
** utterance object is created
*/
adjust = mean_normalize_data(chandata[ii], 0);
/* channorm->adjust[ii]= adjust; */
#if USE_MEDIAN
shift_distribution_counts(chandata[ii], adjust);
#endif
shift_parameters(chandata[ii], adjust);
#if NORM_IN_IMELDA
channorm->imelda_adjust[ii] += adjust;
#else
channorm->adjust[ii] += adjust;
#endif
}
#if NORM_IN_IMELDA
channorm->adj_valid = True;
#if DEBUG
log_report("NORM IML: ");
for (ii = 0; ii < channorm->dim; ii++)
log_report("%d ", channorm->imelda_adjust[ii]);
log_report("\n");
#endif
#else
channorm->adj_valid = False;
#if DEBUG
log_report("NORM ADJ: ");
for (ii = 0; ii < channorm->dim; ii++)
log_report("%d ", channorm->adjust[ii]);
log_report("\n");
#endif
#endif
return;
}
int CA_CalculateUtteranceStatistics(CA_Utterance *hUtt, int start, int end)
{
TRY_CA_EXCEPT
int ii, frames = 0;
frames = get_background_statistics(hUtt->data.gen_utt.frame,
-start, -end,
hUtt->data.gen_utt.backchan,
hUtt->data.gen_utt.num_chan, 1);
/* log_report ("UTT (%d): ", frames); */
for (ii = 0; ii < hUtt->data.gen_utt.num_chan; ii++)
{
evaluate_parameters(hUtt->data.gen_utt.backchan[ii]);
/* log_report ("%d ", hUtt->data.gen_utt.backchan[ii]->mean); */
}
/* log_report ("\n");*/
return (frames);
BEG_CATCH_CA_EXCEPT
END_CATCH_CA_EXCEPT(hUtt)
}
