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import sys
sys.path.append("..")
import os
now_dir = os.getcwd()
from dotenv import load_dotenv
from lib.infer.modules.vc.modules import VC
from assets.configs.config import Config
load_dotenv()
config = Config()
vc = VC(config)
import shutil
import numpy as np
import torch
import soundfile as sf
from gtts import gTTS
import edge_tts
import asyncio
import scipy.io.wavfile as wavfile
import nltk
nltk.download("punkt", quiet=True)
from nltk.tokenize import sent_tokenize
from bark import SAMPLE_RATE
import json
import ssl
from typing import Any, Dict, List, Optional
import asyncio
import aiohttp
import certifi
VOICE_LIST = (
"https://speech.platform.bing.com/consumer/speech/synthesize/"
+ "readaloud/voices/list?trustedclienttoken="
+ "6A5AA1D4EAFF4E9FB37E23D68491D6F4"
)
def get_bark_voice():
mensaje = """
v2/en_speaker_0 English Male
v2/en_speaker_1 English Male
v2/en_speaker_2 English Male
v2/en_speaker_3 English Male
v2/en_speaker_4 English Male
v2/en_speaker_5 English Male
v2/en_speaker_6 English Male
v2/en_speaker_7 English Male
v2/en_speaker_8 English Male
v2/en_speaker_9 English Female
v2/zh_speaker_0 Chinese (Simplified) Male
v2/zh_speaker_1 Chinese (Simplified) Male
v2/zh_speaker_2 Chinese (Simplified) Male
v2/zh_speaker_3 Chinese (Simplified) Male
v2/zh_speaker_4 Chinese (Simplified) Female
v2/zh_speaker_5 Chinese (Simplified) Male
v2/zh_speaker_6 Chinese (Simplified) Female
v2/zh_speaker_7 Chinese (Simplified) Female
v2/zh_speaker_8 Chinese (Simplified) Male
v2/zh_speaker_9 Chinese (Simplified) Female
v2/fr_speaker_0 French Male
v2/fr_speaker_1 French Female
v2/fr_speaker_2 French Female
v2/fr_speaker_3 French Male
v2/fr_speaker_4 French Male
v2/fr_speaker_5 French Female
v2/fr_speaker_6 French Male
v2/fr_speaker_7 French Male
v2/fr_speaker_8 French Male
v2/fr_speaker_9 French Male
v2/de_speaker_0 German Male
v2/de_speaker_1 German Male
v2/de_speaker_2 German Male
v2/de_speaker_3 German Female
v2/de_speaker_4 German Male
v2/de_speaker_5 German Male
v2/de_speaker_6 German Male
v2/de_speaker_7 German Male
v2/de_speaker_8 German Female
v2/de_speaker_9 German Male
v2/hi_speaker_0 Hindi Female
v2/hi_speaker_1 Hindi Female
v2/hi_speaker_2 Hindi Male
v2/hi_speaker_3 Hindi Female
v2/hi_speaker_4 Hindi Female
v2/hi_speaker_5 Hindi Male
v2/hi_speaker_6 Hindi Male
v2/hi_speaker_7 Hindi Male
v2/hi_speaker_8 Hindi Male
v2/hi_speaker_9 Hindi Female
v2/it_speaker_0 Italian Male
v2/it_speaker_1 Italian Male
v2/it_speaker_2 Italian Female
v2/it_speaker_3 Italian Male
v2/it_speaker_4 Italian Male
v2/it_speaker_5 Italian Male
v2/it_speaker_6 Italian Male
v2/it_speaker_7 Italian Female
v2/it_speaker_8 Italian Male
v2/it_speaker_9 Italian Female
v2/ja_speaker_0 Japanese Female
v2/ja_speaker_1 Japanese Female
v2/ja_speaker_2 Japanese Male
v2/ja_speaker_3 Japanese Female
v2/ja_speaker_4 Japanese Female
v2/ja_speaker_5 Japanese Female
v2/ja_speaker_6 Japanese Male
v2/ja_speaker_7 Japanese Female
v2/ja_speaker_8 Japanese Female
v2/ja_speaker_9 Japanese Female
v2/ko_speaker_0 Korean Female
v2/ko_speaker_1 Korean Male
v2/ko_speaker_2 Korean Male
v2/ko_speaker_3 Korean Male
v2/ko_speaker_4 Korean Male
v2/ko_speaker_5 Korean Male
v2/ko_speaker_6 Korean Male
v2/ko_speaker_7 Korean Male
v2/ko_speaker_8 Korean Male
v2/ko_speaker_9 Korean Male
v2/pl_speaker_0 Polish Male
v2/pl_speaker_1 Polish Male
v2/pl_speaker_2 Polish Male
v2/pl_speaker_3 Polish Male
v2/pl_speaker_4 Polish Female
v2/pl_speaker_5 Polish Male
v2/pl_speaker_6 Polish Female
v2/pl_speaker_7 Polish Male
v2/pl_speaker_8 Polish Male
v2/pl_speaker_9 Polish Female
v2/pt_speaker_0 Portuguese Male
v2/pt_speaker_1 Portuguese Male
v2/pt_speaker_2 Portuguese Male
v2/pt_speaker_3 Portuguese Male
v2/pt_speaker_4 Portuguese Male
v2/pt_speaker_5 Portuguese Male
v2/pt_speaker_6 Portuguese Male
v2/pt_speaker_7 Portuguese Male
v2/pt_speaker_8 Portuguese Male
v2/pt_speaker_9 Portuguese Male
v2/ru_speaker_0 Russian Male
v2/ru_speaker_1 Russian Male
v2/ru_speaker_2 Russian Male
v2/ru_speaker_3 Russian Male
v2/ru_speaker_4 Russian Male
v2/ru_speaker_5 Russian Female
v2/ru_speaker_6 Russian Female
v2/ru_speaker_7 Russian Male
v2/ru_speaker_8 Russian Male
v2/ru_speaker_9 Russian Female
v2/es_speaker_0 Spanish Male
v2/es_speaker_1 Spanish Male
v2/es_speaker_2 Spanish Male
v2/es_speaker_3 Spanish Male
v2/es_speaker_4 Spanish Male
v2/es_speaker_5 Spanish Male
v2/es_speaker_6 Spanish Male
v2/es_speaker_7 Spanish Male
v2/es_speaker_8 Spanish Female
v2/es_speaker_9 Spanish Female
v2/tr_speaker_0 Turkish Male
v2/tr_speaker_1 Turkish Male
v2/tr_speaker_2 Turkish Male
v2/tr_speaker_3 Turkish Male
v2/tr_speaker_4 Turkish Female
v2/tr_speaker_5 Turkish Female
v2/tr_speaker_6 Turkish Male
v2/tr_speaker_7 Turkish Male
v2/tr_speaker_8 Turkish Male
v2/tr_speaker_9 Turkish Male
"""
# Dividir el mensaje en líneas
lineas = mensaje.split("\n")
datos_deseados = []
for linea in lineas:
partes = linea.split("\t")
if len(partes) == 3:
clave, _, genero = partes
datos_deseados.append(f"{clave}-{genero}")
return datos_deseados
# ||-----------------------------------------------------------------------------------||
# || Obtained from dependency edge_tts ||
# ||-----------------------------------------------------------------------------------||
async def list_voices(*, proxy: Optional[str] = None) -> Any:
"""
List all available voices and their attributes.
This pulls data from the URL used by Microsoft Edge to return a list of
all available voices.
Returns:
dict: A dictionary of voice attributes.
"""
ssl_ctx = ssl.create_default_context(cafile=certifi.where())
async with aiohttp.ClientSession(trust_env=True) as session:
async with session.get(
VOICE_LIST,
headers={
"Authority": "speech.platform.bing.com",
"Sec-CH-UA": '" Not;A Brand";v="99", "Microsoft Edge";v="91", "Chromium";v="91"',
"Sec-CH-UA-Mobile": "?0",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/91.0.4472.77 Safari/537.36 Edg/91.0.864.41",
"Accept": "*/*",
"Sec-Fetch-Site": "none",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Dest": "empty",
"Accept-Encoding": "gzip, deflate, br",
"Accept-Language": "en-US,en;q=0.9",
},
proxy=proxy,
ssl=ssl_ctx,
) as url:
data = json.loads(await url.text())
return data
async def create(custom_voices: Optional[List[Dict[str, Any]]] = None) -> List[Dict[str, Any]]:
"""
Creates a list of voices with all available voices and their attributes.
"""
voices = await list_voices() if custom_voices is None else custom_voices
voices = [
{**voice, **{"Language": voice["Locale"].split("-")[0]}}
for voice in voices
]
simplified_voices = [
{'ShortName': voice['ShortName'], 'Gender': voice['Gender']}
for voice in voices
]
return simplified_voices
async def loop_main():
voices = await create()
voices_json = json.dumps(voices)
return voices_json
def get_edge_voice():
loop = asyncio.get_event_loop()
voices_json = loop.run_until_complete(loop_main())
voices = json.loads(voices_json)
tts_voice = []
for voice in voices:
short_name = voice['ShortName']
gender = voice['Gender']
formatted_entry = f"{short_name}-{gender}"
tts_voice.append(formatted_entry)
# print(f"{short_name}-{gender}")
return tts_voice
set_bark_voice = get_bark_voice()
set_edge_voice = get_edge_voice()
def update_tts_methods_voice(select_value):
# ["Edge-tts", "RVG-tts", "Bark-tts"]
if select_value == "Edge-tts":
return {"choices": set_edge_voice, "value": "", "__type__": "update"}
elif select_value == "Bark-tts":
return {"choices": set_bark_voice, "value": "", "__type__": "update"}
def custom_voice(
_values, # filter indices
audio_files, # all audio files
model_voice_path="",
transpose=0,
f0method="pm",
index_rate_=float(0.66),
crepe_hop_length_=float(64),
f0_autotune=False,
file_index="",
file_index2="",
):
vc.get_vc(model_voice_path)
for _value_item in _values:
filename = (
"assets/audios/audio_outputs" + audio_files[_value_item]
if _value_item != "converted_tts"
else audio_files[0]
)
# filename = "audio2/"+audio_files[_value_item]
try:
print(audio_files[_value_item], model_voice_path)
except:
pass
info_, (sample_, audio_output_) = vc.vc_single_dont_save(
sid=0,
input_audio_path1=filename, # f"audio2/{filename}",
f0_up_key=transpose, # transpose for m to f and reverse 0 12
f0_file=None,
f0_method=f0method,
file_index=file_index, # dir pwd?
file_index2=file_index2,
# file_big_npy1,
index_rate=index_rate_,
filter_radius=int(3),
resample_sr=int(0),
rms_mix_rate=float(0.25),
protect=float(0.33),
crepe_hop_length=crepe_hop_length_,
f0_autotune=f0_autotune,
f0_min=50,
note_min=50,
f0_max=1100,
note_max=1100,
)
sf.write(
file=filename, # f"audio2/{filename}",
samplerate=sample_,
data=audio_output_,
)
def cast_to_device(tensor, device):
try:
return tensor.to(device)
except Exception as e:
print(e)
return tensor
def __bark__(text, voice_preset):
os.makedirs(os.path.join(now_dir, "tts"), exist_ok=True)
from transformers import AutoProcessor, BarkModel
device = "cuda:0" if torch.cuda.is_available() else "cpu"
dtype = torch.float32 if "cpu" in device else torch.float16
bark_processor = AutoProcessor.from_pretrained(
"suno/bark",
cache_dir=os.path.join(now_dir, "tts", "suno/bark"),
torch_dtype=dtype,
)
bark_model = BarkModel.from_pretrained(
"suno/bark",
cache_dir=os.path.join(now_dir, "tts", "suno/bark"),
torch_dtype=dtype,
).to(device)
# bark_model.enable_cpu_offload()
inputs = bark_processor(text=[text], return_tensors="pt", voice_preset=voice_preset)
tensor_dict = {
k: cast_to_device(v, device) if hasattr(v, "to") else v
for k, v in inputs.items()
}
speech_values = bark_model.generate(**tensor_dict, do_sample=True)
sampling_rate = bark_model.generation_config.sample_rate
speech = speech_values.cpu().numpy().squeeze()
return speech, sampling_rate
def use_tts(
tts_text,
tts_voice,
model_path,
index_path,
transpose,
f0_method,
index_rate,
crepe_hop_length,
f0_autotune,
tts_method,
):
if tts_voice == None:
return
output_folder = "assets/audios/audio-outputs"
os.makedirs(output_folder, exist_ok=True)
output_count = 1 # Contador para nombres de archivo únicos
while True:
converted_tts_filename = os.path.join(output_folder, f"tts_out_{output_count}.wav")
bark_out_filename = os.path.join(output_folder, f"bark_out_{output_count}.wav")
if not os.path.exists(converted_tts_filename) and not os.path.exists(bark_out_filename):
break
output_count += 1
if "SET_LIMIT" == os.getenv("DEMO"):
if len(tts_text) > 60:
tts_text = tts_text[:60]
print("DEMO; limit to 60 characters")
language = tts_voice[:2]
if tts_method == "Edge-tts":
try:
# nest_asyncio.apply() # gradio;not
asyncio.run(
edge_tts.Communicate(
tts_text, "-".join(tts_voice.split("-")[:-1])
).save(converted_tts_filename)
)
except:
try:
tts = gTTS(tts_text, lang=language)
tts.save(converted_tts_filename)
tts.save
print(
f"No audio was received. Please change the tts voice for {tts_voice}. USING gTTS."
)
except:
tts = gTTS("a", lang=language)
tts.save(converted_tts_filename)
print("Error: Audio will be replaced.")
try:
vc.get_vc(model_path)
info_, (sample_, audio_output_) = vc.vc_single_dont_save(
sid=0,
input_audio_path1=converted_tts_filename,
f0_up_key=transpose,
f0_file=None,
f0_method=f0_method,
file_index="",
file_index2=index_path,
index_rate=index_rate,
filter_radius=int(3),
resample_sr=int(0),
rms_mix_rate=float(0.25),
protect=float(0.33),
crepe_hop_length=crepe_hop_length,
f0_autotune=f0_autotune,
f0_min=50,
note_min=50,
f0_max=1100,
note_max=1100,
)
# Genera un nombre de archivo único para el archivo procesado por vc.vc_single_dont_save
vc_output_filename = os.path.join(output_folder, f"converted_tts_{output_count}.wav")
# Guarda el archivo de audio procesado por vc.vc_single_dont_save
wavfile.write(
vc_output_filename,
rate=sample_,
data=audio_output_,
)
return vc_output_filename,converted_tts_filename
except Exception as e:
print(f"{e}")
return None, None
elif tts_method == "Bark-tts":
try:
script = tts_text.replace("\n", " ").strip()
sentences = sent_tokenize(script)
print(sentences)
silence = np.zeros(int(0.25 * SAMPLE_RATE))
pieces = []
for sentence in sentences:
audio_array, _ = __bark__(sentence, tts_voice.split("-")[0])
pieces += [audio_array, silence.copy()]
sf.write(
file=bark_out_filename, samplerate=SAMPLE_RATE, data=np.concatenate(pieces)
)
vc.get_vc(model_path)
info_, (sample_, audio_output_) = vc.vc_single_dont_save(
sid=0,
input_audio_path1=os.path.join(
now_dir, "assets", "audios", "audio-outputs", "bark_out.wav"
), # f"audio2/{filename}",
f0_up_key=transpose, # transpose for m to f and reverse 0 12
f0_file=None,
f0_method=f0_method,
file_index="", # dir pwd?
file_index2=index_path,
# file_big_npy1,
index_rate=index_rate,
filter_radius=int(3),
resample_sr=int(0),
rms_mix_rate=float(0.25),
protect=float(0.33),
crepe_hop_length=crepe_hop_length,
f0_autotune=f0_autotune,
f0_min=50,
note_min=50,
f0_max=1100,
note_max=1100,
)
vc_output_filename = os.path.join(output_folder, f"converted_bark_{output_count}.wav")
# Guarda el archivo de audio procesado por vc.vc_single_dont_save
wavfile.write(
vc_output_filename,
rate=sample_,
data=audio_output_,
)
return vc_output_filename, bark_out_filename
except Exception as e:
print(f"{e}")
return None, None