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import pathlib
import re
from typing import Dict, List
import click
import librosa
import natsort
import numpy
import soundfile
import textgrid
import tqdm
def remove_suffix(string, suffix_pattern):
match = re.search(f'{suffix_pattern}$', string)
if not match:
return string
return string[:-len(match.group())]
@click.command(help='Combine segmented 2-tier TextGrids and wavs into 3-tier TextGrids and long wavs')
@click.option(
'--wavs', required=True,
help='Directory containing the segmented wav files'
)
@click.option(
'--tg', required=False,
help='Directory containing the segmented TextGrid files (defaults to wav directory)'
)
@click.option(
'--out', required=True,
help='Path to output directory for combined files'
)
@click.option(
'--suffix', required=False, default=r'_\d+',
help='Filename suffix pattern for file combination'
)
@click.option(
'--wav_subtype', required=False, default='PCM_16',
help='Wav subtype (defaults to PCM_16)'
)
@click.option(
'--overwrite', is_flag=True,
help='Overwrite existing files'
)
def combine_tg(wavs, tg, out, suffix, wav_subtype, overwrite):
wav_path_in = pathlib.Path(wavs)
tg_path_in = wav_path_in if tg is None else pathlib.Path(tg)
del tg
combined_path_out = pathlib.Path(out)
combined_path_out.mkdir(parents=True, exist_ok=True)
filelist: Dict[str, List[pathlib.Path]] = {}
for tg_file in tg_path_in.glob('*.TextGrid'):
stem = remove_suffix(tg_file.stem, suffix)
if stem not in filelist:
filelist[stem] = [tg_file]
else:
filelist[stem].append(tg_file)
for name, files in tqdm.tqdm(sorted(filelist.items(), key=lambda kv: kv[0])):
wav_segments = []
tg = textgrid.TextGrid()
sentences_tier = textgrid.IntervalTier(name='sentences')
words_tier = textgrid.IntervalTier(name='words')
phones_tier = textgrid.IntervalTier(name='phones')
sentence_start = 0.
sr = None
for tg_file in natsort.natsorted(files):
wav_file = (wav_path_in / tg_file.name).with_suffix('.wav')
waveform, sr_ = librosa.load(wav_file, sr=None)
if sr is None:
sr = sr_
else:
assert sr_ == sr, f'Cannot combine \'{tg_file.stem}\': incompatible samplerate ({sr_} != {sr})'
sentence_end = waveform.shape[0] / sr + sentence_start
wav_segments.append(waveform)
sentences_tier.add(minTime=sentence_start, maxTime=sentence_end, mark=wav_file.stem)
sentence_tg = textgrid.TextGrid()
sentence_tg.read(tg_file)
start = sentence_start
for j, word in enumerate(sentence_tg[0]):
if j == len(sentence_tg[0]) - 1:
end = sentence_end
else:
end = start + word.duration()
words_tier.add(minTime=start, maxTime=end, mark=word.mark)
start = end
start = sentence_start
for j, phone in enumerate(sentence_tg[1]):
if j == len(sentence_tg[1]) - 1:
end = sentence_end
else:
end = start + phone.duration()
phones_tier.add(minTime=start, maxTime=end, mark=phone.mark)
start = end
sentence_start = sentence_end
tg.append(sentences_tier)
tg.append(words_tier)
tg.append(phones_tier)
tg_file_out = combined_path_out / f'{name}.TextGrid'
wav_file_out = tg_file_out.with_suffix('.wav')
if wav_file_out.exists() and not overwrite:
raise FileExistsError(str(wav_file_out))
if tg_file_out.exists() and not overwrite:
raise FileExistsError(str(tg_file_out))
tg.write(tg_file_out)
full_wav = numpy.concatenate(wav_segments)
soundfile.write(wav_file_out, full_wav, samplerate=sr, subtype=wav_subtype)
if __name__ == '__main__':
combine_tg()
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