Spaces:
Runtime error
Runtime error
File size: 4,542 Bytes
f38f846 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
import os
import argparse
import re
from tqdm import tqdm
from random import shuffle
import json
import wave
import diffusion.logger.utils as du
config_template = json.load(open("configs_template/config_template.json"))
pattern = re.compile(r'^[\.a-zA-Z0-9_\/]+$')
def get_wav_duration(file_path):
with wave.open(file_path, 'rb') as wav_file:
# 获取音频帧数
n_frames = wav_file.getnframes()
# 获取采样率
framerate = wav_file.getframerate()
# 计算时长（秒）
duration = n_frames / float(framerate)
return duration
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
parser.add_argument("--source_dir", type=str, default="./dataset/44k", help="path to source dir")
parser.add_argument("--speech_encoder", type=str, default="vec768l12", help="choice a speech encoder|'vec768l12','vec256l9','hubertsoft','whisper-ppg','cnhubertlarge','dphubert','whisper-ppg-large','wavlmbase+'")
parser.add_argument("--vol_aug", action="store_true", help="Whether to use volume embedding and volume augmentation")
args = parser.parse_args()
train = []
val = []
idx = 0
spk_dict = {}
spk_id = 0
for speaker in tqdm(os.listdir(args.source_dir)):
spk_dict[speaker] = spk_id
spk_id += 1
wavs = ["/".join([args.source_dir, speaker, i]) for i in os.listdir(os.path.join(args.source_dir, speaker))]
new_wavs = []
for file in wavs:
if not file.endswith("wav"):
continue
if not pattern.match(file):
print(f"warning：文件名{file}中包含非字母数字下划线，可能会导致错误。（也可能不会）")
if get_wav_duration(file) < 0.3:
print("skip too short audio:", file)
continue
new_wavs.append(file)
wavs = new_wavs
shuffle(wavs)
train += wavs[2:]
val += wavs[:2]
shuffle(train)
shuffle(val)
print("Writing", args.train_list)
with open(args.train_list, "w") as f:
for fname in tqdm(train):
wavpath = fname
f.write(wavpath + "\n")
print("Writing", args.val_list)
with open(args.val_list, "w") as f:
for fname in tqdm(val):
wavpath = fname
f.write(wavpath + "\n")
d_config_template = du.load_config("configs_template/diffusion_template.yaml")
d_config_template["model"]["n_spk"] = spk_id
d_config_template["data"]["encoder"] = args.speech_encoder
d_config_template["spk"] = spk_dict
config_template["spk"] = spk_dict
config_template["model"]["n_speakers"] = spk_id
config_template["model"]["speech_encoder"] = args.speech_encoder
if args.speech_encoder == "vec768l12" or args.speech_encoder == "dphubert" or args.speech_encoder == "wavlmbase+":
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 768
d_config_template["data"]["encoder_out_channels"] = 768
elif args.speech_encoder == "vec256l9" or args.speech_encoder == 'hubertsoft':
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 256
d_config_template["data"]["encoder_out_channels"] = 256
elif args.speech_encoder == "whisper-ppg" or args.speech_encoder == 'cnhubertlarge':
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 1024
d_config_template["data"]["encoder_out_channels"] = 1024
elif args.speech_encoder == "whisper-ppg-large":
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 1280
d_config_template["data"]["encoder_out_channels"] = 1280
if args.vol_aug:
config_template["train"]["vol_aug"] = config_template["model"]["vol_embedding"] = True
print("Writing configs/config.json")
with open("configs/config.json", "w") as f:
json.dump(config_template, f, indent=2)
print("Writing configs/diffusion_template.yaml")
du.save_config("configs/diffusion.yaml",d_config_template)
|