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047092de8e
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c75906462e
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import argparse
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import os
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import re
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import shutil
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import ToJyutping
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def check(str):
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my_re = re.compile(r'[A-Za-z]', re.S)
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res = re.findall(my_re, str)
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if len(res):
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return True
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else:
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return False
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consonants = [
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'p', 'b', 't', 'd', 'ts', 'dz', 'k', 'g', 'kw', 'gw', 'f', 'h', 'l', 'm',
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'ng', 'n', 's', 'y', 'w', 'c', 'z', 'j'
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]
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def get_lines(canton):
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for consonant in consonants:
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if canton.startswith(consonant):
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c, v = canton[:len(consonant)], canton[len(consonant):]
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return canton + ' ' + c + ' ' + v
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return canton + ' ' + canton
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Generate lexicon for Cantonese pinyin to phoneme for MFA")
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parser.add_argument(
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"--output_lexicon", type=str, help="Path to save lexicon.")
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parser.add_argument(
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"--output_wavlabs",
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type=str,
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help="Path of wavs and labs for MFA training.")
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parser.add_argument(
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"--inputs", type=str, nargs="+", help="Path to the cantonese datasets.")
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args = parser.parse_args()
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os.mkdir(args.output_wavlabs)
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utterance_info = []
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all_canton = []
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for input_ in args.inputs:
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utt = "UTTRANSINFO.txt" if "Guangzhou_Cantonese_Scripted_Speech_Corpus_Daily_Use_Sentence" in input_ else "UTTERANCEINFO.txt"
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input_utttxt = os.path.join(input_, utt)
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with open(input_utttxt, 'r') as f:
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utterance_info = f.readlines()[1:]
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for utterance_line in utterance_info:
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_, wav_name, spk, _, text = utterance_line.split('\t')
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text = text.strip().replace(' ', '')
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# check the characters and drop the short text.
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if not check(text) and len(text) > 2:
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source_path = os.path.join(input_, 'WAV', spk, wav_name)
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out_spk_path = os.path.join(args.output_wavlabs, spk)
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os.makedirs(out_spk_path, exist_ok=True)
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target_path = os.path.join(out_spk_path, wav_name)
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shutil.copy(source_path, target_path)
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lab_name = wav_name.split('.')[0] + '.lab'
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lab_target_path = os.path.join(out_spk_path, lab_name)
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canton_list = ToJyutping.get_jyutping_text(text)
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with open(lab_target_path, 'w') as f:
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f.write(canton_list)
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canton_list = canton_list.split(' ')
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all_canton.extend(canton_list)
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all_canton = set(all_canton)
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with open(args.output_lexicon, 'w') as f:
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for canton in all_canton:
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f.write(get_lines(canton) + '\n')
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@ -0,0 +1,34 @@
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EXP_DIR=exp
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mkdir -p $EXP_DIR
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LEXICON_NAME='canton'
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if [ ! -f "$EXP_DIR/$LEXICON_NAME.lexicon" ]; then
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echo "generating lexicon and training data..."
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python local/generate_canton_lexicon_wavlabs.py --output_lexicon "$EXP_DIR/$LEXICON_NAME.lexicon" --output_wavlabs "$EXP_DIR/$LEXICON_NAME"_wavlabs --inputs ~/datasets/Guangzhou_Cantonese_Scripted_Speech_Corpus_Daily_Use_Sentence ~/datasets/Guangzhou_Cantonese_Scripted_Speech_Corpus_in_Vehicle
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echo "lexicon and training data done"
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fi
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MFA_DOWNLOAD_DIR=local/
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if [ ! -f "$MFA_DOWNLOAD_DIR/montreal-forced-aligner_linux.tar.gz" ]; then
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echo "downloading mfa..."
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(cd $MFA_DOWNLOAD_DIR && wget https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/releases/download/v1.0.1/montreal-forced-aligner_linux.tar.gz)
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echo "download mfa done!"
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fi
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if [ ! -d "$MFA_DOWNLOAD_DIR/montreal-forced-aligner" ]; then
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echo "extracting mfa..."
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(cd $MFA_DOWNLOAD_DIR && tar xvf "montreal-forced-aligner_linux.tar.gz")
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echo "extraction done!"
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fi
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export PATH="$MFA_DOWNLOAD_DIR/montreal-forced-aligner/bin"
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if [ ! -d "$EXP_DIR/canton_alignment" ]; then
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echo "Start MFA training..."
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mfa_train_and_align "$EXP_DIR/$LEXICON_NAME"_wavlabs "$EXP_DIR/$LEXICON_NAME.lexicon" $EXP_DIR/canton_alignment -o $EXP_DIR/canton_model --clean --verbose --temp_directory $EXP_DIR/.mfa_train_and_align
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echo "training done!"
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echo "results: $EXP_DIR/canton_alignment"
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echo "model: $EXP_DIR/canton_model"
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fi
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