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beff33fdf9
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beff33fdf9 | ||
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af785e51cf |
3
.gitignore
vendored
3
.gitignore
vendored
@ -1,9 +1,6 @@
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## Ignore Visual Studio temporary files, build results, and
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## files generated by popular Visual Studio add-ons.
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## important ##
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.acoustic_model/forced_alignment_novo.py
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# User-specific files
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*.suo
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*.user
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@ -25,12 +25,12 @@ mapping = convert_xsampa2ipa.load_converter('xsampa', 'ipa', default.ipa_xsampa_
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stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
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phonelist_novo70_ = pd.ExcelFile(default.phonelist_novo70_xlsx)
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df = pd.read_excel(phonelist_novo70_, 'list')
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## novo phoneset
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#translation_key = dict()
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translation_key = dict()
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#phonelist_novo70_ = pd.ExcelFile(default.phonelist_novo70_xlsx)
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#df = pd.read_excel(phonelist_novo70_, 'list')
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## *_simple includes columns which has only one phone in.
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#for ipa, novo70 in zip(df['IPA_simple'], df['novo70_simple']):
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# if not pd.isnull(ipa):
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@ -38,3 +38,18 @@ df = pd.read_excel(phonelist_novo70_, 'list')
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# translation_key[ipa] = novo70
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#phonelist_novo70 = np.unique(list(df['novo70_simple']))
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phoneset_ipa = []
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phoneset_novo70 = []
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with open(default.cmu69_phoneset, "rt", encoding="utf-8") as fin:
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lines = fin.read()
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lines = lines.split('\n')
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for line in lines:
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words = line.split('\t')
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if len(words) > 1:
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novo70 = words[0]
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ipa = words[1]
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phoneset_ipa.append(ipa)
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phoneset_novo70.append(novo70)
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translation_key[ipa] = novo70
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phoneset_ipa = np.unique(phoneset_ipa)
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phoneset_novo70 = np.unique(phonset_novo70)
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@ -3,7 +3,7 @@ import os
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#default_hvite_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'data', 'htk', 'config.HVite')
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cygwin_dir = r'C:\cygwin64\home\Aki\acoustic_model'
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kaldi_dir = r'C:\OneDrive\WSL\kaldi-trunk\egs\fame\s5'
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#config_hcopy = os.path.join(cygwin_dir, 'config', 'config.HCopy')
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#config_train = os.path.join(cygwin_dir, 'config', 'config.train')
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config_hvite = os.path.join(cygwin_dir, 'config', 'config.HVite')
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@ -30,16 +30,11 @@ repo_dir = r'C:\Users\Aki\source\repos'
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ipa_xsampa_converter_dir = os.path.join(repo_dir, 'ipa-xsama-converter')
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forced_alignment_module_dir = os.path.join(repo_dir, 'forced_alignment')
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WSL_dir = r'C:\OneDrive\WSL'
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fame_dir = os.path.join(WSL_dir, 'kaldi-trunk', 'egs', 'fame')
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fame_s5_dir = os.path.join(fame_dir, 's5')
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fame_corpus_dir = os.path.join(fame_dir, 'corpus')
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fame_dir = r'C:\OneDrive\WSL\kaldi-trunk\egs\fame\s5\corpus'
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experiments_dir = r'c:\OneDrive\Research\rug\experiments'
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stimmen_transcription_xlsx = os.path.join(experiments_dir, 'stimmen', 'data', 'Frisian Variants Picture Task Stimmen.xlsx')
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stimmen_data_dir = os.path.join(experiments_dir, 'stimmen', 'data')
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phonelist_friesian_txt = os.path.join(experiments_dir, 'friesian', 'acoustic_model', 'config', 'phonelist_friesian.txt')
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novo_api_dir = os.path.join(WSL_dir, 'python-novo-api')
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cmu69_phoneset = os.path.join(novo_api_dir, 'novoapi', 'asr', 'phoneset', 'en', 'cmu69.phoneset')
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phonelist_novo70_xlsx = os.path.join(experiments_dir, 'Nederlandse phonesets_aki.xlsx')
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@ -30,12 +30,12 @@ htk_dict_dir = os.path.join(default.experiments_dir, 'stimmen', 'dic_short
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fa_dir = os.path.join(default.experiments_dir, 'stimmen', 'FA_44k')
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result_dir = os.path.join(default.experiments_dir, 'stimmen', 'result')
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kaldi_data_dir = os.path.join(default.fame_s5_dir, 'data', 'alignme')
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kaldi_dict_dir = os.path.join(default.fame_s5_dir, 'data', 'local', 'dict')
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kaldi_data_dir = os.path.join(default.kaldi_dir, 'data', 'alignme')
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kaldi_dict_dir = os.path.join(default.kaldi_dir, 'data', 'local', 'dict')
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lexicon_txt = os.path.join(kaldi_dict_dir, 'lexicon.txt')
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#lex_asr = os.path.join(default.fame_corpus_dir, 'lexicon', 'lex.asr')
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#lex_asr_htk = os.path.join(default.fame_corpus_dir, 'lexicon', 'lex.asr_htk')
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#lex_asr = os.path.join(default.fame_dir, 'lexicon', 'lex.asr')
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#lex_asr_htk = os.path.join(default.fame_dir, 'lexicon', 'lex.asr_htk')
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# procedure
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@ -278,8 +278,8 @@ if make_kaldi_lexicon_txt:
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## ======================= load kaldi forced alignment result =======================
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if load_forced_alignment_kaldi:
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phones_txt = os.path.join(default.fame_s5_dir, 'data', 'lang', 'phones.txt')
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merged_alignment_txt = os.path.join(default.fame_s5_dir, 'exp', 'tri1_alignme', 'merged_alignment.txt')
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phones_txt = os.path.join(default.kaldi_dir, 'data', 'lang', 'phones.txt')
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merged_alignment_txt = os.path.join(default.kaldi_dir, 'exp', 'tri1_alignme', 'merged_alignment.txt')
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#filenames = np.load(data_dir + '\\filenames.npy')
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#words = np.load(data_dir + '\\words.npy')
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