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#!/usr/bin/env python
# Copyright (c) 2013, Ondrej Platek, Ufal MFF UK <oplatek@ufal.mff.cuni.cz>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
# WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
# MERCHANTABLITY OR NON-INFRINGEMENT.
# See the Apache 2 License for the specific language governing permissions and
# limitations under the License. #
from __future__ import unicode_literals
from __future__ import division
from __future__ import print_function
from kaldi.utils import load_wav, wst2dict, lattice_to_nbest
from kaldi.decoders import PyOnlineLatgenRecogniser
import sys
import fst
import time
# DEBUG = True
DEBUG = False
def write_decoded(f, wav_name, word_ids, wst):
assert(len(word_ids) > 0)
best_weight, best_path = word_ids[0]
if wst is not None:
decoded = [wst[w] for w in best_path]
else:
decoded = [str(w) for w in best_path]
line = u' '.join([wav_name] + decoded + ['
'])
if DEBUG:
print('%s best path %s' % (wav_name, decoded.encode('UTF-8')))
for i, s in enumerate(word_ids):
if i > 0:
break
print('best path %d: %s' % (i, str(s)))
f.write(line.encode('UTF-8'))
# @profile
def decode(d, pcm):
frame_len = (2 * audio_batch_size) # 16-bit audio so 1 sample = 2 chars
i, decoded_frames, max_end = 0, 0, len(pcm)
start = time.time()
while i * frame_len < len(pcm):
i, begin, end = i + 1, i * frame_len, min(max_end, (i + 1) * frame_len)
audio_chunk = pcm[begin:end]
d.frame_in(audio_chunk)
dec_t = d.decode(max_frames=10)
while dec_t > 0:
decoded_frames += dec_t
dec_t = d.decode(max_frames=10)
print("forward decode: %s secs" % str(time.time() - start))
start = time.time()
d.prune_final()
lik, lat = d.get_lattice()
print("backward decode: %s secs" % str(time.time() - start))
d.reset(keep_buffer_data=False)
return (lat, lik, decoded_frames)
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)
if __name__ == '__main__':
audio_scp, audio_batch_size = sys.argv[1], int(sys.argv[2])
dec_hypo, wst_path = sys.argv[3], sys.argv[4]
argv = sys.argv[5:]
print('Python args: %s' % str(sys.argv), file=sys.stderr)
# open audio_scp, decode and write to dec_hypo file
with open(audio_scp, 'rb') as r:
with open(dec_hypo, 'wb') as w:
lines = r.readlines()
scp = [tuple(line.strip().split(' ', 1)) for line in lines]
decode_wrap(argv, audio_batch_size, scp, w, wst_path)
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