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)