def run(self):
while True:
time.sleep(0.1)
self._user_control()
new_frames = self.d.decode(max_frames=10)
while new_frames > 0:
self.utt_frames += new_frames
new_frames = self.d.decode(max_frames=10)
if self.utt_end or self.dialog_end:
start = time.time()
self.d.prune_final()
prob, lat = self.d.get_lattice()
# lat.write('live-demo-recorded.fst')
nbest = lattice_to_nbest(lat, n=10)
if nbest:
best_prob, best_path = nbest[0]
decoded = ' '.join([wst[w] for w in best_path])
else:
decoded = 'Empty hypothesis'
print("%s secs, frames: %d, prob: %f, %s " % (
str(time.time() - start), self.utt_frames, prob, decoded))
self.utt_frames = 0
self.d.reset(keep_buffer_data=False)
if self.dialog_end:
self.save_wav()
break
def run(self):
while True:
time.sleep(0.1)
self._user_control()
new_frames = self.d.decode(max_frames=10)
while new_frames > 0:
self.utt_frames += new_frames
new_frames = self.d.decode(max_frames=10)
if self.utt_end or self.dialog_end:
start = time.time()
self.d.prune_final()
prob, lat = self.d.get_lattice()
# lat.write('live-demo-recorded.fst')
nbest = lattice_to_nbest(lat, n=10)
if nbest:
best_prob, best_path = nbest[0]
decoded = ' '.join([wst[w] for w in best_path])
else:
decoded = 'Empty hypothesis'
print(
"%s secs, frames: %d, prob: %f, %s " %
(str(time.time() - start), self.utt_frames, prob, decoded))
self.utt_frames = 0
self.d.reset(keep_buffer_data=False)
if self.dialog_end:
self.save_wav()
break
def nbest_hypotheses(n=10):
global recogniser
recogniser.prune_final()
utt_lik, lat = recogniser.get_lattice()
recogniser.reset()
return [(prob, path_to_text(path))
for (prob, path) in lattice_to_nbest(lat, n=10)]
def get_lat():
global dec_frames
d.prune_final()
lik, lat = d.get_lattice()
nbest = lattice_to_nbest(lat, n=10)
nbest_s = '\n'.join(["%0.3f %s" % (prob, ' '.join([wst[i] for i in ids])) for (prob, ids) in nbest])
dec_frames, result = 0, jsonify(nbest=nbest_s, dec_frames=dec_frames)
print 'DEBUG', dec_frames
d.reset(keep_buffer_data=False)
return result
def get_lat():
global dec_frames
d.prune_final()
lik, lat = d.get_lattice()
nbest = lattice_to_nbest(lat, n=10)
nbest_s = '\n'.join([
"%0.3f %s" % (prob, ' '.join([wst[i] for i in ids]))
for (prob, ids) in nbest
])
dec_frames, result = 0, jsonify(nbest=nbest_s, dec_frames=dec_frames)
print 'DEBUG', dec_frames
d.reset(keep_buffer_data=False)
return result
def decode_wrap(argv, audio_batch_size, wav_paths, file_output, wst_path=None):
wst = wst2dict(wst_path)
d = PyOnlineLatgenRecogniser()
d.setup(argv)
for wav_name, wav_path in wav_paths:
sw, sr = 2, 16000 # 16-bit audio so 1 sample_width = 2 chars
pcm = load_wav(wav_path, def_sample_width=sw, def_sample_rate=sr)
print('%s has %f sec' % (wav_name, (float(len(pcm)) / sw) / sr))
lat, lik, decoded_frames = decode(d, pcm)
lat.isyms = lat.osyms = fst.read_symbols_text(wst_path)
if DEBUG:
with open('pykaldi_%s.svg' % wav_name, 'w') as f:
f.write(lat._repr_svg_())
lat.write('%s_pykaldi.fst' % wav_name)
print(
"Log-likelihood per frame for utterance %s is %f over %d frames" %
(wav_name, int(lik / decoded_frames), decoded_frames))
word_ids = lattice_to_nbest(lat, n=10)
write_decoded(file_output, wav_name, word_ids, wst)
def decode_wrap(argv, audio_batch_size, wav_paths,
file_output, wst_path=None):
wst = wst2dict(wst_path)
d = PyOnlineLatgenRecogniser()
d.setup(argv)
for wav_name, wav_path in wav_paths:
sw, sr = 2, 16000 # 16-bit audio so 1 sample_width = 2 chars
pcm = load_wav(wav_path, def_sample_width=sw, def_sample_rate=sr)
print '%s has %f sec' % (wav_name, (float(len(pcm)) / sw) / sr)
lat, lik, decoded_frames = decode(d, pcm)
lat.isyms = lat.osyms = fst.read_symbols_text(wst_path)
if DEBUG:
with open('pykaldi_%s.svg' % wav_name, 'w') as f:
f.write(lat._repr_svg_())
lat.write('%s_pykaldi.fst' % wav_name)
print "Log-likelihood per frame for utterance %s is %f over %d frames" % (
wav_name, (lik / decoded_frames), decoded_frames)
word_ids = lattice_to_nbest(lat, n=10)
write_decoded(file_output, wav_name, word_ids, wst)
