sp is added to the model.
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yemaozi88
parent
f6e7c8eefa
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@ -25,13 +25,17 @@ make_label = 0 # it takes roughly 4800 sec on Surface pro 2.
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make_htk_files = 0
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extract_features = 0
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flat_start = 0
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train_model_without_sp = 1
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train_model_without_sp = 0
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add_sp = 0
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train_model_with_sp = 0
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# pre-defined values.
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dataset_list = ['devel', 'test', 'train']
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hmmdefs_name = 'hmmdefs'
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proto_name = 'proto39'
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lexicon_asr = os.path.join(default.fame_dir, 'lexicon', 'lex.asr')
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lexicon_oov = os.path.join(default.fame_dir, 'lexicon', 'lex.oov')
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@ -41,7 +45,8 @@ config_hcopy = os.path.join(config_dir, 'config.HCopy')
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config_train = os.path.join(config_dir, 'config.train')
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global_ded = os.path.join(config_dir, 'global.ded')
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mkphones_led = os.path.join(config_dir, 'mkphones.led')
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prototype = os.path.join(config_dir, 'proto39')
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sil_hed = os.path.join(config_dir, 'sil.hed')
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prototype = os.path.join(config_dir, proto_name)
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model_dir = os.path.join(default.htk_dir, 'model')
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@ -55,6 +60,7 @@ lexicon_htk = os.path.join(lexicon_dir, 'lex.htk')
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phonelist_txt = os.path.join(config_dir, 'phonelist.txt')
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model0_dir = os.path.join(model_dir, 'hmm0')
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model1_dir = os.path.join(model_dir, 'hmm1')
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feature_dir = os.path.join(default.htk_dir, 'mfc')
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if not os.path.exists(feature_dir):
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@ -66,6 +72,13 @@ label_dir = os.path.join(default.htk_dir, 'label')
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if not os.path.exists(label_dir):
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os.makedirs(label_dir)
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## training
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hcompv_scp_train = os.path.join(tmp_dir, 'train.scp')
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mlf_file_train = os.path.join(label_dir, 'train_phone.mlf')
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## train without sp
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niter_max = 10
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## ======================= make lexicon for HTK =======================
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if make_lexicon:
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@ -95,6 +108,7 @@ if make_lexicon:
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## ======================= make label files =======================
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if make_label:
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# train_2002_gongfansaken_10347.lab is empty. should be removed.
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for dataset in dataset_list:
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timer_start = time.time()
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print("==== making label files on dataset {}".format(dataset))
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@ -216,45 +230,111 @@ if extract_features:
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## ======================= flat start monophones =======================
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if flat_start:
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hcompv_scp = os.path.join(tmp_dir, 'test.scp')
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timer_start = time.time()
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print('==== flat start ====')
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pyhtk.flat_start(config_train, hcompv_scp, model0_dir, prototype)
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pyhtk.flat_start(config_train, hcompv_scp_train, model0_dir, prototype)
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# allocate mean & variance to all phones in the phone list
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print('>>> allocating mean & variance to all phones in the phone list...')
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pyhtk.create_hmmdefs(
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os.path.join(model0_dir, 'proto39'),
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os.path.join(model0_dir, proto_name),
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os.path.join(model0_dir, 'hmmdefs'),
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phonelist_txt)
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# make macros
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print('>>> making macros...')
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with open(os.path.join(model0_dir, 'vFloors')) as f:
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lines = f.read()
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with open(os.path.join(model0_dir, 'macros'), 'wb') as f:
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f.write(bytes('~o <MFCC_0_D_A> <VecSize> 39\n' + lines, 'ascii'))
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print("elapsed time: {}".format(time.time() - timer_start))
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## ======================= estimate monophones =======================
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## ======================= train model without short pause =======================
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if train_model_without_sp:
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hcompv_scp = os.path.join(tmp_dir, 'test.scp')
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mlf_file = os.path.join(label_dir, 'test_phone.mlf')
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output_dir = os.path.join(model_dir, 'hmm1')
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fh.make_new_directory(output_dir)
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fh.make_new_directory(model1_dir)
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print('==== train model without sp ====')
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if not os.path.exists(os.path.join(output_dir, 'iter0')):
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shutil.copytree(model0_dir, os.path.join(output_dir, 'iter0'))
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niter = 1
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for niter in range(1, 5):
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if not os.path.exists(os.path.join(model1_dir, 'iter0')):
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shutil.copytree(model0_dir, os.path.join(model1_dir, 'iter0'))
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for niter in range(1, niter_max):
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timer_start = time.time()
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hmm_n = 'iter' + str(niter)
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hmm_n_pre = 'iter' + str(niter-1)
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modeln_dir = os.path.join(output_dir, hmm_n)
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modeln_dir_pre = os.path.join(output_dir, hmm_n_pre)
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modeln_dir = os.path.join(model1_dir, hmm_n)
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modeln_dir_pre = os.path.join(model1_dir, hmm_n_pre)
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# re-estimation
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fh.make_new_directory(modeln_dir)
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pyhtk.re_estimation(
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config_train,
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os.path.join(modeln_dir_pre, 'proto39'),
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os.path.join(modeln_dir_pre, 'macros'),
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os.path.join(modeln_dir_pre, hmmdefs_name),
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modeln_dir,
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hcompv_scp, phonelist_txt,
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mlf_file=mlf_file)
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hcompv_scp_train, phonelist_txt,
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mlf_file=mlf_file_train)
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print("elapsed time: {}".format(time.time() - timer_start))
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## ======================= adding sp to the model =======================
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if add_sp:
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print('==== adding sp to the model ====')
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# make model with sp.
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print('>>> modifying the last model in the previous step...')
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modeln_dir_pre = os.path.join(model1_dir, 'iter'+str(niter_max-1))
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modeln_dir = modeln_dir_pre.replace('iter' + str(niter_max-1), 'iter' + str(niter_max))
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fh.make_new_directory(modeln_dir)
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shutil.copy(
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os.path.join(modeln_dir_pre, 'macros'),
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os.path.join(modeln_dir, 'macros'))
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shutil.copy(
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os.path.join(modeln_dir_pre, hmmdefs_name),
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os.path.join(modeln_dir, hmmdefs_name))
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## =======================
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## manually make changes to modeln_dir/hmmdefs
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## =======================
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# add states 'sil'.
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# http://www.f.waseda.jp/yusukekondo/htk.html#flat_start_estimation
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#shutil.copy(
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# os.path.join(model_dir, 'hmmdefs.txt'),
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# os.path.join(modeln_dir, hmmdefs_name))
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#hmmdefs_file_pre = os.path.join(modeln_dir_pre, hmmdefs_name)
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hmmdefs_file = os.path.join(modeln_dir, hmmdefs_name)
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macros_file = os.path.join(modeln_dir, 'macros')
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#with open(hmmdefs_file_pre) as f:
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# lines = f.read()
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#lines_ = lines.split('~h ')
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#sil_model = [line for line in lines_ if line.split('\n')[0].replace('"', '') == 'sil'][0]
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# update hmmdefs and macros.
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print('>>> updating hmmdefs and macros...')
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modeln_dir_pre = modeln_dir
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modeln_dir = modeln_dir.replace('iter' + str(niter_max), 'iter' + str(niter_max+1))
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fh.make_new_directory(modeln_dir)
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pyhtk.include_sil_in_hmmdefs(macros_file, hmmdefs_file, modeln_dir, sil_hed, phonelist_txt)
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## ======================= train model with short pause =======================
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if train_model_with_sp:
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print('==== train model with sp ====')
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for niter in range(niter_max+1, niter_max*2+1):
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timer_start = time.time()
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hmm_n = 'iter' + str(niter)
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hmm_n_pre = 'iter' + str(niter-1)
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modeln_dir = os.path.join(model1_dir, hmm_n)
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modeln_dir_pre = os.path.join(model1_dir, hmm_n_pre)
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# re-estimation
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fh.make_new_directory(modeln_dir)
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pyhtk.re_estimation(
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config_train,
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os.path.join(modeln_dir_pre, 'macros'),
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os.path.join(modeln_dir_pre, hmmdefs_name),
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modeln_dir,
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hcompv_scp_train, phonelist_txt,
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mlf_file=mlf_file_train)
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print("elapsed time: {}".format(time.time() - timer_start))
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