htk_config.load_object_vals(options)
name, model, scp, dict, lm = args[:5]
recognizer = HTK_recognizer(htk_config, name, model, scp, dict, lm)
recognizer.recognize(None, 'baseline')
if len(args) > 6:
for s in [32, 64, 128, 256, 384, 512, 640, 768, 896, 1024]:
tscp, tmlf = args[5:7]
recognizer.add_adaptation(tscp,
tmlf,
num_speaker_chars=options.eval_speaker_chars)
recognizer.add_adaptation(tscp,
tmlf,
num_speaker_chars=options.eval_speaker_chars,
num_nodes=s)
recognizer.recognize(None, 'transform.size-%d' % s)
recognizer.clear_adaptations()
# recognizer.add_adaptation(scp,recognizer.name+'.transform.mlf',num_speaker_chars=options.eval_speaker_chars)
# recognizer.add_adaptation(scp,recognizer.name+'.transform.mlf',num_speaker_chars=options.eval_speaker_chars,num_nodes=64)
#
# recognizer.recognize(None,'transform_stack')
htk_config.load_config_vals(options.config)
htk_config.load_object_vals(options)
name,model,scp,dict,lm = args[:5]
recognizer = HTK_recognizer(htk_config,name,model,scp,dict,lm)
recognizer.recognize(None,'baseline')
if len(args) > 6:
for s in [32,64,128,256,384,512,640,768,896,1024]:
tscp, tmlf = args[5:7]
recognizer.add_adaptation(tscp,tmlf,num_speaker_chars=options.eval_speaker_chars)
recognizer.add_adaptation(tscp,tmlf,num_speaker_chars=options.eval_speaker_chars,num_nodes=s)
recognizer.recognize(None,'transform.size-%d'%s)
recognizer.clear_adaptations()
# recognizer.add_adaptation(scp,recognizer.name+'.transform.mlf',num_speaker_chars=options.eval_speaker_chars)
# recognizer.add_adaptation(scp,recognizer.name+'.transform.mlf',num_speaker_chars=options.eval_speaker_chars,num_nodes=64)
#
# recognizer.recognize(None,'transform_stack')
# t_files = t_files[:options.num_adaptation_files]
for t in t_files:
f = splitext(basename(t))[0]
mlf.transcriptions[HTK_transcription.WORD][
"%s_%s" %
(sp, f)] = mlf.transcriptions[HTK_transcription.WORD][f]
new_f = join(file_dir, "%s_%s" % (sp, basename(t)))
symlink(t, new_f)
print >> transform_desc, new_f
mlf.write_mlf(transform_mlf, target=HTK_transcription.WORD)
recognizer.add_adaptation(transform_scp,
transform_mlf,
num_speaker_chars=options.transform_speaker_chars)
recognizer.add_adaptation(transform_scp,
transform_mlf,
num_speaker_chars=options.transform_speaker_chars,
num_nodes=options.tree_size)
recognizer.recognize(None, 'neighbour_transform')
if options.dostack:
recognizer.add_adaptation(scp,
recognizer.name + '.neighbour_transform.mlf',
num_speaker_chars=options.eval_speaker_chars,
files_per_speaker=options.num_adaptation_files)
recognizer.add_adaptation(scp,
recognizer.name + '.neighbour_transform.mlf',
t_files.extend(transform_files[n])
shuffle(t_files)
# if options.num_adaptation_files > 0:
# t_files = t_files[:options.num_adaptation_files]
for t in t_files:
f = splitext(basename(t))[0]
mlf.transcriptions[HTK_transcription.WORD]["%s_%s"%(sp,f)] = mlf.transcriptions[HTK_transcription.WORD][f]
new_f = join(file_dir,"%s_%s"%(sp,basename(t)))
symlink(t,new_f)
print >> transform_desc, new_f
mlf.write_mlf(transform_mlf,target=HTK_transcription.WORD)
recognizer.add_adaptation(transform_scp,transform_mlf,num_speaker_chars=options.transform_speaker_chars)
recognizer.add_adaptation(transform_scp,transform_mlf,num_speaker_chars=options.transform_speaker_chars,num_nodes=options.tree_size)
recognizer.recognize(None,'neighbour_transform')
if options.dostack:
recognizer.add_adaptation(scp,recognizer.name+'.neighbour_transform.mlf',num_speaker_chars=options.eval_speaker_chars,files_per_speaker=options.num_adaptation_files)
recognizer.add_adaptation(scp,recognizer.name+'.neighbour_transform.mlf',num_speaker_chars=options.eval_speaker_chars,num_nodes=64,files_per_speaker=options.num_adaptation_files)
#
recognizer.recognize(None,'neighbour_transform_stack.%d'%options.num_adaptation_files)
