persian-tts-demo / pmt2 /prepare_data.py
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initial commit
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import json
import re
import csv
import shutil
import os
import argparse
main_path = os.getcwd()
def get_duration(row):
phone_durs = row.split()
dur_sum = 0
for phone_dur in phone_durs:
if phone_dur == '|':
continue
else:
phone_dur = phone_dur.split('[')
dur = float(phone_dur[1][:-1])/1000
dur_sum += dur
return dur_sum
def prepare_data_for_model(path, duration_lim):
f = open(path, 'r')
data = csv.DictReader(f)
data_lines = []
for row in data:
dur = get_duration(row['phenome'])
if dur > duration_lim:
continue
phoneme = row['phenome']
utterance_name = row['seg_id']
speaker_id = row['speaker_id']
phoneme = re.sub("\[([0-9]+)\]", '', phoneme)
phoneme = re.sub("\s+\|\s+", ' ', phoneme)
data_lines.append([phoneme, utterance_name, speaker_id])
f.close()
return data_lines
def save_files(train_data, test_data, data_path):
for line in train_data:
try:
original = os.path.join(data_path, 'train_wav/{}.wav'.format(line[1]))
target = os.path.join(main_path, 'dataset/persian_data/train_data/speaker-{0}/book-1/utterance-{1}.wav'.format(line[2], line[1]))
os.makedirs(os.path.dirname(target), exist_ok=True)
shutil.copyfile(original, target)
except Exception as e:
print(e)
return False
path = os.path.join(main_path, 'dataset/persian_data/train_data/speaker-{0}/book-1/utterance-{1}.txt'.format(line[2], line[1]))
with open(path, 'w') as fp:
fp.write(line[0])
for line in test_data:
try:
original = os.path.join(data_path, 'test_wav/{}.wav'.format(line[1]))
target = os.path.join(main_path, 'dataset/persian_data/test_data/speaker-{0}/book-1/utterance-{1}.wav'.format(line[2], line[1]))
os.makedirs(os.path.dirname(target), exist_ok=True)
shutil.copyfile(original, target)
except Exception as e:
print(e)
return False
path = os.path.join(main_path, 'dataset/persian_data/test_data/speaker-{0}/book-1/utterance-{1}.txt'.format(line[2], line[1]))
with open(path, 'w') as fp:
fp.write(line[0])
return True
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--data_path', required=True)
args = parser.parse_args()
data_path = args.data_path
if os.path.isfile(os.path.join(data_path, 'train_info.csv')):
train_data_path = os.path.join(data_path, 'train_info.csv')
else:
print('data_path is not correct!')
return -1
if os.path.isfile(os.path.join(data_path, 'test_info.csv')):
test_data_path = os.path.join(data_path, 'test_info.csv')
else:
print('data_path is not correct!')
return -1
train_data = prepare_data_for_model(train_data_path, 12)
test_data = prepare_data_for_model(test_data_path, 15)
print('number of train data: ' + str(len(train_data)))
print('number of test data: ' + str(len(test_data)))
res = save_files(train_data, test_data, data_path)
if res:
print('Data is created.')
if __name__ == "__main__":
main()