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import pathlib |
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import click |
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import librosa |
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import soundfile |
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import textgrid |
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import tqdm |
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@click.command(help='Slice 3-tier TextGrids and long recordings into segmented 2-tier TextGrids and wavs') |
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@click.option( |
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'--wavs', required=True, |
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help='Directory containing the segmented wav files' |
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) |
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@click.option( |
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'--tg', required=False, |
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help='Directory containing the segmented TextGrid files (defaults to wav directory)' |
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) |
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@click.option( |
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'--out', required=True, |
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help='Path to output directory for combined files' |
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) |
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@click.option( |
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'--preserve_sentence_names', is_flag=True, |
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help='Whether to use sentence marks as filenames (will be re-numbered by default)' |
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) |
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@click.option( |
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'--digits', required=False, type=int, default=3, |
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help='Number of suffix digits (defaults to 3, will be padded with zeros on the left)' |
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) |
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@click.option( |
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'--wav_subtype', required=False, default='PCM_16', |
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help='Wav subtype (defaults to PCM_16)' |
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) |
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@click.option( |
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'--overwrite', is_flag=True, |
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help='Overwrite existing files' |
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) |
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def slice_tg(wavs, tg, out, preserve_sentence_names, digits, wav_subtype, overwrite): |
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wav_path_in = pathlib.Path(wavs) |
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tg_path_in = wav_path_in if tg is None else pathlib.Path(tg) |
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del tg |
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sliced_path_out = pathlib.Path(out) |
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sliced_path_out.mkdir(parents=True, exist_ok=True) |
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for tg_file in tqdm.tqdm(tg_path_in.glob('*.TextGrid')): |
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tg = textgrid.TextGrid() |
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tg.read(tg_file) |
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wav, sr = librosa.load((wav_path_in / tg_file.name).with_suffix('.wav'), sr=None) |
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sentences_tier = tg[0] |
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words_tier = tg[1] |
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phones_tier = tg[2] |
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idx = 0 |
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for sentence in sentences_tier: |
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if sentence.mark == '': |
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continue |
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sentence_tg = textgrid.TextGrid() |
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sentence_words_tier = textgrid.IntervalTier(name='words') |
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sentence_phones_tier = textgrid.IntervalTier(name='phones') |
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for word in words_tier: |
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min_time = max(sentence.minTime, word.minTime) |
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max_time = min(sentence.maxTime, word.maxTime) |
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if min_time >= max_time: |
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continue |
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sentence_words_tier.add( |
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minTime=min_time - sentence.minTime, maxTime=max_time - sentence.minTime, mark=word.mark |
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) |
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for phone in phones_tier: |
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min_time = max(sentence.minTime, phone.minTime) |
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max_time = min(sentence.maxTime, phone.maxTime) |
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if min_time >= max_time: |
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continue |
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sentence_phones_tier.add( |
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minTime=min_time - sentence.minTime, maxTime=max_time - sentence.minTime, mark=phone.mark |
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) |
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sentence_tg.append(sentence_words_tier) |
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sentence_tg.append(sentence_phones_tier) |
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if preserve_sentence_names: |
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tg_file_out = sliced_path_out / f'{sentence.mark}.TextGrid' |
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wav_file_out = tg_file_out.with_suffix('.wav') |
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else: |
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tg_file_out = sliced_path_out / f'{tg_file.stem}_{str(idx).zfill(digits)}.TextGrid' |
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wav_file_out = tg_file_out.with_suffix('.wav') |
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if tg_file_out.exists() and not overwrite: |
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raise FileExistsError(str(tg_file_out)) |
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if wav_file_out.exists() and not overwrite: |
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raise FileExistsError(str(wav_file_out)) |
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sentence_tg.write(tg_file_out) |
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sentence_wav = wav[int(sentence.minTime * sr): min(wav.shape[0], int(sentence.maxTime * sr) + 1)] |
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soundfile.write( |
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wav_file_out, |
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sentence_wav, samplerate=sr, subtype=wav_subtype |
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) |
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idx += 1 |
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if __name__ == '__main__': |
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slice_tg() |
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