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@ -22,30 +22,27 @@ from htk import pyhtk |
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# procedure |
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make_lexicon = 0 |
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make_label = 0 # it takes roughly 4800 sec on Surface pro 2. |
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make_htk_files = 0 |
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make_mlf = 0 |
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extract_features = 0 |
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flat_start = 0 |
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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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train_model_with_sp_align_mlf = 1 |
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train_model_with_sp_align_mlf = 0 |
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train_triphone = 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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proto_name = 'proto' |
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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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config_dir = os.path.join(default.htk_dir, 'config') |
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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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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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@ -53,25 +50,20 @@ model_dir = os.path.join(default.htk_dir, 'model') |
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# directories / files to be made. |
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lexicon_dir = os.path.join(default.htk_dir, 'lexicon') |
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lexicon_htk_asr = os.path.join(lexicon_dir, 'lex.htk_asr') |
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lexicon_htk_oov = os.path.join(lexicon_dir, 'lex.htk_oov') |
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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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#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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os.makedirs(feature_dir) |
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fh.make_new_directory(feature_dir, existing_dir='leave') |
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tmp_dir = os.path.join(default.htk_dir, 'tmp') |
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if not os.path.exists(tmp_dir): |
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os.makedirs(tmp_dir) |
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fh.make_new_directory(tmp_dir, existing_dir='leave') |
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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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fh.make_new_directory(label_dir, existing_dir='leave') |
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## training |
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hcompv_scp_train = os.path.join(tmp_dir, 'train.scp') |
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@ -98,20 +90,21 @@ if make_lexicon: |
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# therefore there is no overlap between lex_asr and lex_oov. |
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fame_functions.combine_lexicon(lexicon_htk_asr, lexicon_htk_oov, lexicon_htk) |
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## ======================= |
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## manually make changes to the pronunciation dictionary and save it as lex.htk |
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## ======================= |
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## fixing the lexicon for HTK. |
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# (1) Replace all tabs with single space; |
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# (2) Put a '\' before any dictionary entry beginning with single quote |
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#http://electroblaze.blogspot.nl/2013/03/understanding-htk-error-messages.html |
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# http://electroblaze.blogspot.nl/2013/03/understanding-htk-error-messages.html |
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print('>>> fixing the lexicon...') |
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fame_functions.fix_lexicon(lexicon_htk) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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## intialize the instance for HTK. |
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chtk = pyhtk.HTK(config_dir, fame_asr.phoneset_htk, lexicon_htk) |
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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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@ -120,7 +113,7 @@ if make_label: |
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wav_dir_ = os.path.join(default.fame_dir, 'fame', 'wav', dataset) |
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label_dir_ = os.path.join(label_dir, dataset) |
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dictionary_file = os.path.join(label_dir_, 'temp.dic') |
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fh.make_new_directory(label_dir_) |
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fh.make_new_directory(label_dir_, existing_dir='leave') |
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# list of scripts |
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with open(script_list, "rt", encoding="utf-8") as fin: |
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@ -135,56 +128,48 @@ if make_label: |
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sentence_htk = fame_functions.word2htk(sentence) |
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wav_file = os.path.join(wav_dir_, filename + '.wav') |
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if os.path.exists(wav_file) and pyhtk.can_be_ascii(sentence_htk) == 0: |
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if pyhtk.create_dictionary_without_log( |
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sentence_htk, global_ded, dictionary_file, lexicon_htk) == 0: |
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if os.path.exists(wav_file) and chtk.can_be_ascii(sentence_htk) == 0: |
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if chtk.get_number_of_missing_words( |
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sentence_htk, dictionary_file) == 0: |
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# when the file name is too long, HDMan command does not work. |
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# therefore first temporary dictionary_file is made, then renamed. |
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shutil.move(dictionary_file, os.path.join(label_dir_, filename + '.dic')) |
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label_file = os.path.join(label_dir_, filename + '.lab') |
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pyhtk.create_label_file(sentence_htk, label_file) |
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chtk.create_label_file(sentence_htk, label_file) |
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else: |
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os.remove(dictionary_file) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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## ======================= make other required files ======================= |
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if make_htk_files: |
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## ======================= make master label files ======================= |
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if make_mlf: |
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timer_start = time.time() |
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print("==== making files required for HTK ====") |
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print("==== making master label files ====") |
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print(">>> making a phonelist...") |
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pyhtk.create_phonelist_file(fame_asr.phoneset_htk, phonelist_txt) |
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# train_2002_gongfansaken_10347.lab is empty. should be removed. |
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empty_lab_file = os.path.join(label_dir, 'train', 'train_2002_gongfansaken_10347.lab') |
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empty_dic_file = empty_lab_file.replace('.lab', '.dic') |
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if os.path.exists(empty_lab_file): |
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os.remove(empty_lab_file) |
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if os.path.exists(empty_dic_file): |
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os.remove(empty_dic_file) |
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for dataset in dataset_list: |
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wav_dir_ = os.path.join(default.fame_dir, 'fame', 'wav', dataset) |
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#wav_dir_ = os.path.join(default.fame_dir, 'fame', 'wav', dataset) |
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feature_dir_ = os.path.join(feature_dir, dataset) |
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label_dir_ = os.path.join(label_dir, dataset) |
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mlf_word = os.path.join(label_dir, dataset + '_word.mlf') |
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mlf_phone = os.path.join(label_dir, dataset + '_phone.mlf') |
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#print(">>> making a script file for {}...".format(dataset)) |
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#listdir = glob.glob(os.path.join(wav_dir_, '*.dic')) |
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#mfc_list = [filename.replace(wav_dir_, feature_dir_).replace('.dic', '.mfc') for filename in listdir] |
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#hcompv_scp = os.path.join(tmp_dir, dataset + '.scp') |
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#with open(hcompv_scp, 'wb') as f: |
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# f.write(bytes('\n'.join(mfc_list) + '\n', 'ascii')) |
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print(">>> making a mlf file for {}...".format(dataset)) |
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lab_list = glob.glob(os.path.join(label_dir_, '*.lab')) |
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with open(mlf_word, 'wb') as fmlf: |
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fmlf.write(bytes('#!MLF!#\n', 'ascii')) |
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for label_file in lab_list: |
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filename = os.path.basename(label_file) |
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fmlf.write(bytes('\"*/{}\"\n'.format(filename), 'ascii')) |
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with open(label_file) as flab: |
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lines = flab.read() |
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fmlf.write(bytes(lines + '.\n', 'ascii')) |
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print(">>> generating phone level transcription for {}...".format(dataset)) |
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pyhtk.mlf_word2phone(lexicon_htk, mlf_phone, mlf_word, mkphones_led) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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print(">>> generating a word level mlf file for {}...".format(dataset)) |
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chtk.label2mlf(label_dir_, mlf_word) |
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print(">>> generating a phone level mlf file for {}...".format(dataset)) |
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chtk.mlf_word2phone(mlf_phone, mlf_word) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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## ======================= extract features ======================= |
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@ -196,7 +181,7 @@ if extract_features: |
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wav_dir_ = os.path.join(default.fame_dir, 'fame', 'wav', dataset) |
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label_dir_ = os.path.join(label_dir, dataset) |
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feature_dir_ = os.path.join(feature_dir, dataset) |
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fh.make_new_directory(feature_dir_) |
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fh.make_new_directory(feature_dir_, existing_dir='delete') |
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# a script file for HCopy |
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print(">>> making a script file for HCopy...") |
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@ -212,12 +197,15 @@ if extract_features: |
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os.path.join(wav_dir_, os.path.basename(lab_file).replace('.lab', '.wav')) + '\t' |
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+ os.path.join(feature_dir_, os.path.basename(lab_file).replace('.lab', '.mfc')) |
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for lab_file in lab_list] |
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if os.path.exists(empty_mfc_file): |
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os.remove(empty_mfc_file) |
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with open(hcopy_scp.name, 'wb') as f: |
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f.write(bytes('\n'.join(feature_list), 'ascii')) |
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# extract features. |
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print(">>> extracting features on {}...".format(dataset)) |
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pyhtk.wav2mfc(config_hcopy, hcopy_scp.name) |
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chtk.wav2mfc(hcopy_scp.name) |
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os.remove(hcopy_scp.name) |
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# make hcompv.scp. |
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@ -235,21 +223,18 @@ if extract_features: |
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if flat_start: |
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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_train, model0_dir, prototype) |
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feature_size = 39 |
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model0_dir = os.path.join(model_dir, 'hmm0') |
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fh.make_new_directory(model0_dir, existing_dir='leave') |
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chtk.flat_start(hcompv_scp_train, model0_dir, feature_size) |
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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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chtk.create_hmmdefs( |
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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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os.path.join(model0_dir, 'hmmdefs') |
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) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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@ -362,4 +347,24 @@ if train_model_with_sp_align_mlf: |
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hcompv_scp_train, phonelist_txt, |
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mlf_file=mlf_file_train_aligned, |
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macros=os.path.join(modeln_dir_pre, 'macros')) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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print("elapsed time: {}".format(time.time() - timer_start)) |
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# train triphone. |
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if train_triphone: |
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triphone_mlf = os.path.join(default.htk_dir, 'label', 'train_triphone.mlf') |
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macros = os.path.join(model_dir, 'hmm1_tri', 'iter0', 'macros') |
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hmmdefs = os.path.join(model_dir, 'hmm1_tri', 'iter0', 'hmmdefs') |
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model_out_dir = os.path.join(model_dir, 'hmm1_tri', 'iter1') |
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run_command([ |
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'HERest', '-B', |
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'-C', config_train, |
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'-I', triphone_mlf, |
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'-t', '250.0', '150.0', '1000.0', |
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'-s', 'stats' |
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'-S', hcompv_scp_train, |
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'-H', macros, |
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'-H', hmmdefs, |
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'-M', model_out_dir, |
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os.path.join(config_dir, 'triphonelist.txt') |
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]) |
yemaozi88
3 years ago