def diarization(protocol,
subset,
hypotheses,
greedy=False,
collar=0.0,
skip_overlap=False):
options = {
'collar': collar,
'skip_overlap': skip_overlap,
'parallel': True
}
metrics = {
'purity': DiarizationPurity(**options),
'coverage': DiarizationCoverage(**options)
}
if greedy:
metrics['error'] = GreedyDiarizationErrorRate(**options)
else:
metrics['error'] = DiarizationErrorRate(**options)
reports = get_reports(protocol, subset, hypotheses, metrics)
report = metrics['error'].report(display=False)
purity = metrics['purity'].report(display=False)
coverage = metrics['coverage'].report(display=False)
report['purity', '%'] = purity[metrics['purity'].name, '%']
report['coverage', '%'] = coverage[metrics['coverage'].name, '%']
columns = list(report.columns)
report = report[[columns[0]] + columns[-2:] + columns[1:-2]]
report = reindex(report)
summary = 'Diarization ({0:s}collar = {1:g} ms{2})'.format(
'greedy, ' if greedy else '', 1000 * collar,
', no overlap' if skip_overlap else '')
headers = [summary] + \
[report.columns[i][0] for i in range(3)] + \
['%' if c[1] == '%' else c[0] for c in report.columns[3:]]
print(
tabulate(report,
headers=headers,
tablefmt="simple",
floatfmt=".2f",
numalign="decimal",
stralign="left",
missingval="",
showindex="default",
disable_numparse=False))
def get_diarization_metrics(reference, hypothesis, uem=None):
metric_dict = {}
metric = DiarizationErrorRate()
met = metric(reference, hypothesis, uem=uem)
metric_dict[metric.metric_name()] = met
metric = DiarizationCompleteness()
met = metric(reference, hypothesis, uem=uem)
metric_dict[metric.metric_name()] = met
metric = DiarizationCoverage()
met = metric(reference, hypothesis, uem=uem)
metric_dict[metric.metric_name()] = met
metric = DiarizationPurity()
met = metric(reference, hypothesis, uem=uem)
metric_dict[metric.metric_name()] = met
metric = DiarizationHomogeneity()
met = metric(reference, hypothesis, uem=uem)
metric_dict[metric.metric_name()] = met
return metric_dict
def test_coverage(reference, hypothesis):
diarizationCoverage = DiarizationCoverage()
coverage = diarizationCoverage(reference, hypothesis)
npt.assert_almost_equal(coverage, 0.7586, decimal=3)