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import collections |
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import os |
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import re |
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import shutil |
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import subprocess |
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import argparse |
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from pathlib import Path |
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from praatio.textgrid import openTextgrid, Textgrid, IntervalTier |
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korean_root = '/mnt/d/Data/speech/korean_corpora' |
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seoul_corpus = os.path.join(korean_root, 'seoul_corpus') |
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original_textgrids = os.path.join(seoul_corpus, 'original') |
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training_textgrids = os.path.join(seoul_corpus, 'seoul_corpus_benchmark') |
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reference_dir = os.path.join(seoul_corpus, 'seoul_reference_alignments') |
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speaker_info = {} |
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def fix_sample_rate(benchmark_directory: Path): |
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for speaker in os.listdir(benchmark_directory): |
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speaker_dir = os.path.join(benchmark_directory, speaker) |
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if not os.path.isdir(speaker_dir): |
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continue |
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for file in os.listdir(speaker_dir): |
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if 'resampled' in file: |
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os.remove(file) |
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if file.endswith('.flac') and 'resampled' not in file: |
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path = os.path.join(speaker_dir, file) |
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resampled_file = path.replace('.flac', '_resampled.flac') |
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subprocess.check_call(['sox', path, '-r', '16000', resampled_file]) |
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os.remove(path) |
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os.rename(resampled_file, path) |
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def fix_textgrids(original_directory: Path, benchmark_directory: Path, reference_directory: Path): |
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for file in os.listdir(original_directory): |
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if os.path.isdir(os.path.join(original_directory, file)): |
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continue |
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speaker = file[:3] |
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speaker_gender = file[3] |
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speaker_age = file[4:6] |
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print(speaker, speaker_gender, speaker_age) |
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speaker_info[speaker] = {'gender': speaker_gender, 'age':speaker_age} |
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speaker_directory = os.path.join(benchmark_directory, speaker) |
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reference_speaker_directory = os.path.join(reference_directory, speaker) |
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os.makedirs(speaker_directory, exist_ok=True) |
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os.makedirs(reference_speaker_directory, exist_ok=True) |
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if not file.endswith('.TextGrid'): |
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shutil.move(os.path.join(original_directory, file), os.path.join(speaker_directory, file)) |
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continue |
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tg_path = os.path.join(original_directory, file) |
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tg = openTextgrid(tg_path, includeEmptyIntervals=False, duplicateNamesMode='rename') |
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orth = tg._tierDict['utt.prono.'] |
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new_intervals = [] |
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new_tg_path = os.path.join(speaker_directory, file) |
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reference_tg_path = os.path.join(reference_speaker_directory, file) |
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new_tg = Textgrid(minTimestamp=tg.minTimestamp, maxTimestamp=tg.maxTimestamp) |
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word_intervals = [] |
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for interval in orth._entries: |
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if re.match(r'^<[^>]+>$', interval.label): |
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continue |
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text = interval.label.replace('<VOCNOISE>', '') |
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if not text: |
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continue |
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begin = max(interval.start - 0.2, 0) |
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end = min(interval.end + 0.2, orth.maxTimestamp) |
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if new_intervals and begin <= new_intervals[-1][1]: |
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new_intervals[-1][1] = end |
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new_intervals[-1][2] += ' ' + text |
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else: |
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new_intervals.append([begin, end, text]) |
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word_intervals.append((interval.start, interval.end, text)) |
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tier = IntervalTier(speaker, new_intervals,minT=tg.minTimestamp, maxT=tg.maxTimestamp) |
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new_tg.addTier(tier) |
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new_tg.save(new_tg_path,includeBlankSpaces=True, format='short_textgrid') |
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reference_tg = Textgrid(minTimestamp=tg.minTimestamp, maxTimestamp=tg.maxTimestamp) |
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phone_intervals = [] |
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for interval in tg._tierDict['phoneme']._entries: |
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if interval.label in {'<IVER>', '<SIL>', '<VOCNOISE>', '<NOISE>'}: |
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continue |
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text = interval.label |
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if text.startswith('<'): |
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text = 'spn' |
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phone_intervals.append((interval.start, interval.end, text)) |
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word_tier = IntervalTier('words', word_intervals, minT=tg.minTimestamp, maxT=tg.maxTimestamp) |
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phone_tier = IntervalTier('phones', phone_intervals, minT=tg.minTimestamp, maxT=tg.maxTimestamp) |
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reference_tg.addTier(word_tier) |
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reference_tg.addTier(phone_tier) |
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reference_tg.save(reference_tg_path, format='short_textgrid', includeBlankSpaces=True) |
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def parse_directory(original_directory: Path, benchmark_directory: Path, reference_directory: Path): |
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fix_textgrids(original_directory, benchmark_directory, reference_directory) |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser( |
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prog='create_seoul_benchmark', |
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description='Creates two directories of TextGrid files for use with MFA, ' |
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'one as input with utterances (benchmark) and one for use in reference alignments (reference)') |
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parser.add_argument('original_directory') |
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parser.add_argument('benchmark_directory') |
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parser.add_argument('reference_directory') |
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args = parser.parse_args() |
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parse_directory( |
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Path(args.original_directory), |
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Path(args.benchmark_directory), |
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Path(args.reference_directory) |
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) |
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