#!/usr/bin/env python # Copyright (c) 2013, Ondrej Platek, Ufal MFF UK # # 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 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 = [unicode(w) for w in best_path] line = u' '.join([wav_name] + decoded + ['\n']) 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, (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 >> sys.stderr, 'Python args: %s' % str(sys.argv) # 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)