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同步操作将从 小乐major/VoiceprintRecognition-Pytorch 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
确定后同步将在后台操作,完成时将刷新页面,请耐心等待。
import json
import os
from random import sample
from tqdm import tqdm
import librosa
import numpy as np
from pydub import AudioSegment
from utils.reader import load_audio
# 生成数据列表
def get_data_list(infodata_path, list_path, zhvoice_path):
with open(infodata_path, 'r', encoding='utf-8') as f:
lines = f.readlines()
f_train = open(os.path.join(list_path, 'train_list.txt'), 'w')
f_test = open(os.path.join(list_path, 'test_list.txt'), 'w')
sound_sum = 0
speakers = []
speakers_dict = {}
for line in tqdm(lines):
line = json.loads(line.replace('\n', ''))
duration_ms = line['duration_ms']
if duration_ms < 1300:
continue
speaker = line['speaker']
if speaker not in speakers:
speakers_dict[speaker] = len(speakers)
speakers.append(speaker)
label = speakers_dict[speaker]
sound_path = os.path.join(zhvoice_path, line['index'])
save_path = "%s.wav" % sound_path[:-4]
if not os.path.exists(save_path):
try:
wav = AudioSegment.from_mp3(sound_path)
wav.export(save_path, format="wav")
os.remove(sound_path)
except Exception as e:
print('数据出错:%s, 信息:%s' % (sound_path, e))
continue
if sound_sum % 200 == 0:
f_test.write('%s\t%d\n' % (save_path.replace('\\', '/'), label))
else:
f_train.write('%s\t%d\n' % (save_path.replace('\\', '/'), label))
sound_sum += 1
f_test.close()
f_train.close()
# 删除错误音频
def remove_error_audio(data_list_path):
with open(data_list_path, 'r', encoding='utf-8') as f:
lines = f.readlines()
lines1 = []
for line in tqdm(lines):
audio_path, _ = line.split('\t')
try:
spec_mag = load_audio(audio_path)
lines1.append(line)
except Exception as e:
print(audio_path)
print(e)
with open(data_list_path, 'w', encoding='utf-8') as f:
for line in lines1:
f.write(line)
if __name__ == '__main__':
get_data_list('dataset/zhvoice/text/infodata.json', 'dataset', 'dataset/zhvoice')
remove_error_audio('dataset/train_list.txt')
remove_error_audio('dataset/test_list.txt')
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