96 lines
2.4 KiB
Python
96 lines
2.4 KiB
Python
|
import os
|
||
|
|
import json
|
||
|
|
import torch
|
||
|
|
|
||
|
|
from tqdm.auto import tqdm
|
||
|
|
from pathlib import Path
|
||
|
|
from vall_e.emb.g2p import encode as valle_phonemize
|
||
|
|
from vall_e.emb.qnt import encode_from_file as valle_quantize, _replace_file_extension
|
||
|
|
|
||
|
|
device = "cuda"
|
||
|
|
|
||
|
|
target = "in"
|
||
|
|
|
||
|
|
audio_map = {}
|
||
|
|
text_map = {}
|
||
|
|
|
||
|
|
data = {}
|
||
|
|
|
||
|
|
for season in os.listdir(f"./{target}/"):
|
||
|
|
if not os.path.isdir(f"./{target}/{season}/"):
|
||
|
|
continue
|
||
|
|
|
||
|
|
for episode in os.listdir(f"./{target}/{season}/"):
|
||
|
|
if not os.path.isdir(f"./{target}/{season}/{episode}/"):
|
||
|
|
continue
|
||
|
|
|
||
|
|
for filename in os.listdir(f"./{target}/{season}/{episode}/"):
|
||
|
|
path = f'./{target}/{season}/{episode}/{filename}'
|
||
|
|
attrs = filename.split("_")
|
||
|
|
timestamp = f'{attrs[0]}h{attrs[1]}m{attrs[2]}s'
|
||
|
|
|
||
|
|
key = f'{episode}_{timestamp}'
|
||
|
|
|
||
|
|
if filename[-5:] == ".flac":
|
||
|
|
name = attrs[3]
|
||
|
|
emotion = attrs[4]
|
||
|
|
quality = attrs[5]
|
||
|
|
|
||
|
|
audio_map[key] = {
|
||
|
|
"path": path,
|
||
|
|
'episode': episode,
|
||
|
|
"name": name,
|
||
|
|
"emotion": emotion,
|
||
|
|
"quality": quality,
|
||
|
|
"timestamp": timestamp,
|
||
|
|
}
|
||
|
|
|
||
|
|
elif filename[-4:] == ".txt":
|
||
|
|
text_map[key] = open(path, encoding="utf-8").read()
|
||
|
|
txts = {}
|
||
|
|
wavs = []
|
||
|
|
|
||
|
|
for key, entry in audio_map.items():
|
||
|
|
path = entry['path']
|
||
|
|
name = entry['name']
|
||
|
|
emotion = entry['emotion']
|
||
|
|
quality = entry['quality']
|
||
|
|
episode = entry['episode']
|
||
|
|
path = entry['path']
|
||
|
|
timestamp = entry['timestamp']
|
||
|
|
transcription = text_map[key]
|
||
|
|
if name not in data:
|
||
|
|
data[name] = {}
|
||
|
|
os.makedirs(f'./training/{name}/', exist_ok=True)
|
||
|
|
os.makedirs(f'./voices/{name}/', exist_ok=True)
|
||
|
|
|
||
|
|
key = f'{episode}_{timestamp}.flac'
|
||
|
|
os.rename(path, f'./voices/{name}/{key}')
|
||
|
|
|
||
|
|
data[name][key] = {
|
||
|
|
"segments": [],
|
||
|
|
"language": "en",
|
||
|
|
"text": transcription,
|
||
|
|
"misc": {
|
||
|
|
"emotion": emotion,
|
||
|
|
"quality": quality,
|
||
|
|
"timestamp": timestamp,
|
||
|
|
"episode": episode,
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
path = f'./voices/{name}/{key}'
|
||
|
|
txts[path] = transcription
|
||
|
|
wavs.append(Path(path))
|
||
|
|
|
||
|
|
for name in data.keys():
|
||
|
|
open(f"./training/{name}/whisper.json", "w", encoding="utf-8").write( json.dumps( data[name], indent='\t' ) )
|
||
|
|
|
||
|
|
for key, text in tqdm(txts.items(), desc="Phonemizing..."):
|
||
|
|
path = Path(key)
|
||
|
|
phones = valle_phonemize(text)
|
||
|
|
open(_replace_file_extension(path, ".phn.txt"), "w", encoding="utf-8").write(" ".join(phones))
|
||
|
|
|
||
|
|
for path in tqdm(wavs, desc="Quantizing..."):
|
||
|
|
qnt = valle_quantize(path, device=device)
|
||
|
|
torch.save(qnt.cpu(), _replace_file_extension(path, ".qnt.pt"))
|