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import collections
import re
import argparse
from bs4 import BeautifulSoup as bs
from praatio import textgrid as tgio
from praatio.utilities.constants import Interval
import soundfile
from pathlib import Path
def parse_directory(
original_directory: Path,
benchmark_directory: Path,
reference_directory: Path,
training_directory: Path
):
benchmark_directory.mkdir(parents=True, exist_ok=True)
reference_directory.mkdir(parents=True, exist_ok=True)
training_directory.mkdir(parents=True, exist_ok=True)
talk_to_speaker = collections.defaultdict(set)
with open(original_directory.joinpath('speaker_data.dat'), 'r', encoding='shift_jis') as f:
for line in f:
line = line.strip()
if not line:
continue
line = line.split()
try:
speaker_id = int(line[0])
except:
continue
talk_ids = line[-1]
for t_id in talk_ids.split(':'):
talk_to_speaker[t_id].add(speaker_id)
for k,v in talk_to_speaker.items():
if len(v) > 1:
print(k,v)
for transcription_path in original_directory.iterdir():
if transcription_path.suffix != '.xml':
continue
talk_name = transcription_path.stem
duration = soundfile.info(transcription_path.with_suffix('.wav')).duration
benchmark_path = benchmark_directory.joinpath(talk_name + '.TextGrid')
reference_path = reference_directory.joinpath(talk_name + '.TextGrid')
training_path = training_directory.joinpath(talk_name + '.TextGrid')
if False and benchmark_path.exists():
continue
print(transcription_path.name)
benchmark_tg = tgio.Textgrid(minTimestamp=0.0, maxTimestamp=duration)
reference_tg = tgio.Textgrid(minTimestamp=0.0, maxTimestamp=duration)
with (open(transcription_path, 'r', encoding='utf8') as f):
content = bs(f.read(), 'xml')
talks = content.findAll('Talk')
for talk in talks:
speaker_id = 'CSJ_' + talk.attrs['SpeakerID']
benchmark_tier = tgio.IntervalTier(speaker_id,[], minT=0.0, maxT=duration)
reference_word_tier = tgio.IntervalTier(f"{speaker_id} - words",[], minT=0.0, maxT=duration)
reference_phone_tier = tgio.IntervalTier(f"{speaker_id} - phones",[], minT=0.0, maxT=duration)
alternate_speaker = None
if len(talk_to_speaker[talk_name]) > 1:
alternate_speaker = [x for x in talk_to_speaker[talk_name] if x != int(talk.attrs['SpeakerID'])][0]
alternate_speaker = f"CSJ_{alternate_speaker}"
alternate_benchmark_tier = tgio.IntervalTier(alternate_speaker,[], minT=0.0, maxT=duration)
alternate_reference_word_tier = tgio.IntervalTier(f"{alternate_speaker} - words",[], minT=0.0, maxT=duration)
alternate_reference_phone_tier = tgio.IntervalTier(f"{alternate_speaker} - phones",[], minT=0.0, maxT=duration)
utterance_intervals = talk.findAll('IPU')
has_reference = False
for utterance in utterance_intervals:
transcription = ''
utt_begin = float(utterance.attrs['IPUStartTime'])
utt_end = float(utterance.attrs['IPUEndTime'])
channel = 0 if utterance.attrs['Channel'] == 'L' else 1
long_words = utterance.findAll('LUW')
skip = False
for long_word in long_words:
word = ''
short_words = long_word.findAll('SUW')
word_begin = None
word_end = None
if skip:
break
for short_word in short_words:
if '(R' in short_word.attrs['OrthographicTranscription'] or \
'(?' in short_word.attrs['OrthographicTranscription'] or \
short_word.attrs['OrthographicTranscription'] in {'<FV>'}:
skip = True
break
word += short_word.attrs['OrthographicTranscription']
moras = short_word.findAll('Mora')
for mora in moras:
phonemes = mora.findAll('Phoneme')
for phoneme in phonemes:
phones = phoneme.findAll('Phone')
phone_label = phoneme.attrs["PhonemeEntity"]
begin = None
end = None
for p in phones:
if p.attrs['PhoneEndTime'] is None:
continue
if begin is None:
begin = float(p.attrs['PhoneStartTime'])
if p.attrs['PhoneEndTime'] is not None:
end = float(p.attrs['PhoneEndTime'])
has_reference = True
if word_begin is None:
word_begin = begin
word_end = end
if not word.startswith('(D') and begin != end and phones:
if channel == 0 and alternate_speaker is not None:
alternate_reference_phone_tier.insertEntry(Interval(begin, end, phone_label))
else:
reference_phone_tier.insertEntry(Interval(begin, end, phone_label))
if skip:
continue
word = word.replace(')', '')
if word.startswith('(D'):
word = "<cutoff>"
elif word.startswith('(?'):
word = "<unk>"
elif word.startswith('(A'):
word = word.split(maxsplit=1)[-1].split(';')[0].replace('．', '点')
while any(word.startswith(x) for x in ['(F', '(M', '(O']):
word = word.split(maxsplit=1)[-1]
word = re.sub(r'\(D (\(\?.*?\))?.*?\)', '<unk>', word)
word = re.sub(r'\(A ([^;]+?)?;.*?\)', r'\1', word).replace('．', '点')
word = re.sub(r'\([FM] (.*?)\)', r'\1', word)
transcription += word
if word_begin is None:
continue
if word == "<cutoff>":
if channel == 0 and alternate_speaker is not None:
alternate_reference_phone_tier.insertEntry(Interval(word_begin, word_end, "spn"))
else:
reference_phone_tier.insertEntry(Interval(word_begin, word_end, "spn"))
if channel == 0 and alternate_speaker is not None:
alternate_reference_word_tier.insertEntry(Interval(word_begin, word_end, word))
else:
reference_word_tier.insertEntry(Interval(word_begin, word_end, word))
if not skip and transcription:
if channel == 1 and alternate_speaker is not None:
alternate_benchmark_tier.insertEntry(Interval(utt_begin, utt_end, transcription))
else:
benchmark_tier.insertEntry(Interval(utt_begin, utt_end, transcription))
benchmark_tg.addTier(benchmark_tier)
reference_tg.addTier(reference_word_tier)
reference_tg.addTier(reference_phone_tier)
if alternate_speaker is not None:
benchmark_tg.addTier(alternate_benchmark_tier)
reference_tg.addTier(alternate_reference_word_tier)
reference_tg.addTier(alternate_reference_phone_tier)
if has_reference:
reference_tg.save(
str(reference_path),
"long_textgrid",
includeBlankSpaces=True)
benchmark_tg.save(
str(benchmark_path),
"long_textgrid",
includeBlankSpaces=True)
benchmark_tg.save(
str(training_path),
"long_textgrid",
includeBlankSpaces=True)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
prog='create_seoul_benchmark',
description='Creates two directories of TextGrid files for use with MFA, '
'one as input with utterances (benchmark) and one for use in reference alignments (reference)')
parser.add_argument('original_directory')
parser.add_argument('benchmark_directory')
parser.add_argument('reference_directory')
parser.add_argument('training_directory')
args = parser.parse_args()
parse_directory(
Path(args.original_directory),
Path(args.benchmark_directory),
Path(args.reference_directory),
Path(args.training_directory),
)
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