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import pathlib
import click
import matplotlib.pyplot as plt
import tqdm
import distribution
# noinspection PyShadowingBuiltins
@click.command(help='Validate transcription labels')
@click.option('--dir', required=True, help='Path to the segments directory')
@click.option('--dictionary', required=True, help='Path to the dictionary file')
def validate_labels(dir, dictionary):
# Load dictionary
dict_path = pathlib.Path(dictionary)
with open(dict_path, 'r', encoding='utf8') as f:
rules = [ln.strip().split('\t') for ln in f.readlines()]
dictionary = {}
phoneme_set = set()
for r in rules:
phonemes = r[1].split()
dictionary[r[0]] = phonemes
phoneme_set.update(phonemes)
# Run checks
check_failed = False
covered = set()
phoneme_map = {}
for ph in sorted(phoneme_set):
phoneme_map[ph] = 0
segments_dir = pathlib.Path(dir)
filelist = list(segments_dir.glob('*.wav'))
for file in tqdm.tqdm(filelist):
filename = file.stem
annotation = file.with_suffix('.lab')
if not annotation.exists():
print(f'No annotation found for \'{filename}\'!')
check_failed = True
continue
with open(annotation, 'r', encoding='utf8') as f:
syllables = f.read().strip().split()
if not syllables:
print(f'Annotation file \'{annotation}\' is empty!')
check_failed = True
else:
oov = []
for s in syllables:
if s not in dictionary:
oov.append(s)
else:
for ph in dictionary[s]:
phoneme_map[ph] += 1
covered.update(dictionary[s])
if oov:
print(f'Syllable(s) {oov} not allowed in annotation file \'{annotation}\'')
check_failed = True
# Phoneme coverage
uncovered = phoneme_set - covered
if uncovered:
print(f'The following phonemes are not covered!')
print(sorted(uncovered))
print('Please add more recordings to cover these phonemes.')
check_failed = True
if not check_failed:
print('All annotations are well prepared.')
phoneme_list = sorted(phoneme_set)
phoneme_counts = [phoneme_map[ph] for ph in phoneme_list]
distribution.draw_distribution(
title='Phoneme Distribution Summary',
x_label='Phoneme',
y_label='Number of occurrences',
items=phoneme_list,
values=phoneme_counts
)
phoneme_summary = segments_dir / 'phoneme_distribution.jpg'
plt.savefig(fname=phoneme_summary,
bbox_inches='tight',
pad_inches=0.25)
print(f'Phoneme distribution summary saved to {phoneme_summary}')
if __name__ == '__main__':
validate_labels()
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