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#!/usr/bin/env python
# (c) 2015--2018 NovoLanguage, author: David A. van Leeuwen
import codecs
def print_header(output, begin, end, nr_tiers):
print >> output, 'File type = "ooTextFile"'
print >> output, 'Object class = "TextGrid"'
print >> output, ''
print >> output, 'xmin = %s' % begin
print >> output, 'xmax = %s' % end
print >> output, 'tiers? <exists>'
print >> output, 'size = %d' % nr_tiers
print >> output, 'item []:'
def print_info_tier(output, title, begin, end, label):
print >> output, '\titem [%d]:' % 0
print >> output, '\t\tclass = "IntervalTier"'
print >> output, '\t\tname = "%s"' % title
print >> output, '\t\txmin = %s' % begin
print >> output, '\t\txmax = %s' % end
print >> output, '\t\tintervals: size = %d' % 1
print >> output, '\t\tintervals [1]:'
print >> output, '\t\t\txmin = %s' % begin
print >> output, '\t\t\txmax = %s' % end
print >> output, '\t\t\ttext = "%s"' % label
def print_tier(output, title, begin, end, segs, format, formatter):
print >> output, '\titem [%d]:' % 0
print >> output, '\t\tclass = "IntervalTier"'
print >> output, '\t\tname = "%s"' % title
print >> output, '\t\txmin = %s' % begin
print >> output, '\t\txmax = %s' % end
print >> output, '\t\tintervals: size = %d' % len(segs)
count = 1
for seg in segs:
#print seg
print >> output, '\t\tintervals [%d]:' % count
print >> output, '\t\t\txmin = %s' % repr(int(seg['begin']) / 100.0)
print >> output, '\t\t\txmax = %s' % repr(int(seg['end']) / 100.0)
string = '\t\t\ttext = "' + format + '"'
print >> output, string % formatter(seg['label'])
count += 1
def seg2tg(fname, segments):
if not segments:
return
output = codecs.open(fname, "w", encoding="utf-8")
confidences = []
word_labels = []
phones = []
for s in segments:
conf = s.llh if hasattr(s, "llh") else s.score
confidences.append({'begin': s.begin, 'end': s.end, 'label': conf})
word_labels.append({'begin': s.begin, 'end': s.end, 'label': s.label})
for p in s.phones:
phones.append({'begin': p.begin, 'end': p.end, 'label': p.label})
begin = repr(int(segments[0].begin) / 100.0)
end = repr(int(segments[-1].end) / 100.0)
nr_tiers = 3
print_header(output, begin, end, nr_tiers)
#print_tier(output, "confidence", begin, end, confidences, ('%.3f', lambda x: x))
#print_tier(output, "words", begin, end, word_labels, ('%s', lambda x: x))
#print_tier(output, "phones", begin, end, phones, ('%s', lambda x: x))
print_tier(output, "confidence", begin, end, confidences, '%.3f', lambda x: x)
print_tier(output, "words", begin, end, word_labels, '%s', lambda x: x)
print_tier(output, "phones", begin, end, phones, '%s', lambda x: x)
output.close()