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import os
import uuid
import numpy as np
import torch
import soundfile as sf
from gtts import gTTS
import edge_tts
from inference import Inference
import asyncio
from elevenlabs import voices, generate, save
from elevenlabs.api.error import UnauthenticatedRateLimitError
# Not working in windows
import platform
COQUI_LANGUAGES = []
if platform.system() != 'Windows':
from neon_tts_plugin_coqui import CoquiTTS
# CoquiTTS
COQUI_LANGUAGES = list(CoquiTTS.langs.keys())
coquiTTS = CoquiTTS()
# Elevenlabs
ELEVENLABS_VOICES_RAW = voices()
def get_elevenlabs_voice_names():
elevenlabs_voice_names = []
for voice in ELEVENLABS_VOICES_RAW:
elevenlabs_voice_names.append(voice.name)
return elevenlabs_voice_names
ELEVENLABS_VOICES_NAMES = get_elevenlabs_voice_names()
def tts_infer(tts_text, model_url, tts_method, tts_model, tts_api_key, language):
if not tts_text:
return 'Primero escribe el texto que quieres convertir.', None
if not tts_model and tts_method != 'CoquiTTS':
return 'Selecciona un modelo TTS antes de convertir.', None
f0_method = "harvest"
output_folder = "audios"
os.makedirs(output_folder, exist_ok=True)
converted_tts_filename = os.path.join(output_folder, f"tts_out_{uuid.uuid4()}.wav")
success = False
if tts_method == "Edge-tts":
language = tts_model[:2]
try:
asyncio.run(
edge_tts.Communicate(
tts_text, "-".join(tts_model.split("-")[:-1])
).save(converted_tts_filename)
)
success = True
except Exception as e:
print("ERROR", e)
try:
tts = gTTS(tts_text, lang=language)
tts.save(converted_tts_filename)
print(
f"No audio was received. Please change the tts voice for {tts_model}. USING gTTS."
)
success = True
except:
tts = gTTS("a", lang=language)
tts.save(converted_tts_filename)
print("Error: Audio will be replaced.")
success = False
# if tts_method == "Tortoise":
# api.TextToSpeech()
if tts_method == "CoquiTTS":
if platform.system() == 'Windows':
return "Funcionalidad no disponible en windows", None
print(tts_text, language)
# return output
coquiTTS.get_tts(tts_text, converted_tts_filename, speaker = {"language" : language})
success = True
if tts_method == 'ElevenLabs':
if len(tts_text) > 2499:
return "El límite de cuentas no logeadas es de 2500 caracteres.", None
try:
audio = generate(
text=tts_text,
voice=tts_model,
model="eleven_multilingual_v2",
api_key=tts_api_key
)
save(audio=audio, filename=converted_tts_filename)
success = True
except UnauthenticatedRateLimitError:
return "Necesitas configurar tu API Key para usar elevenlabs", None
if not model_url:
return 'Pon la url del modelo si quieres aplicarle otro tono.', converted_tts_filename
if success:
inference = Inference(
model_name=model_url,
f0_method=f0_method,
source_audio_path=converted_tts_filename,
output_file_name=os.path.join("./audio-outputs", os.path.basename(converted_tts_filename)),
)
output = inference.run()
if os.path.exists(converted_tts_filename):
os.remove(converted_tts_filename)
if os.path.exists(os.path.join("weights", inference.model_name)):
os.remove(os.path.join("weights", inference.model_name))
if 'success' in output and output['success']:
return output, output['file']
else:
return output, None
else:
return "Ocurrió un error durante la conversión", None
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