def compact_hyp(hyp_path, comp_hyp_path):
d = DefaultOrderedDict(list)
with open(hyp_path, 'rb') as hyp:
for line in hyp:
tmp = line.split()
name, dec = tmp[0], tmp[1:]
d[name].extend(dec)
with open(comp_hyp_path, 'wb') as w:
for wav, dec_list in d.iteritems():
w.write('%s %s\n' % (wav, ' '.join(dec_list)))
def compact_hyp(hyp_path, comp_hyp_path):
"""Converts transcriptions of single hypotheses on multiple lines
to one hypothesis per line.
Read from hyp_path file and save the results to comp_hyp_path
Args:
hyp_path(str): path to file with hypotheses on multiple lines
comp_hyp_path(str): path to save the hypotheses one on each line
"""
d = DefaultOrderedDict(list)
with open(hyp_path, 'rb') as hyp:
for line in hyp:
tmp = line.split()
name, dec = tmp[0], tmp[1:]
d[name].extend(dec)
with open(comp_hyp_path, 'wb') as w:
for wav, dec_list in d.iteritems():
w.write('%s %s\n' % (wav, ' '.join(dec_list)))