import gradio as gr
import sys
from TTS.api import TTS
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1")
tts.to("cuda")
def predict(prompt, language, audio_file_pth, mic_file_path, use_mic, agree):
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,
)
try:
tts.tts_to_file(
text=prompt,
file_path="output.wav",
speaker_wav=speaker_wav,
language=language,
)
except RuntimeError:
if "device-side" in e.message:
# 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")
print(e.message)
sys.exit("Exit due to cuda device-assert")
raise
return (
gr.make_waveform(
audio="output.wav",
),
"output.wav",
)
else:
gr.Warning("Please accept the Terms & Condition!")
return (
None,
None,
)
title = "Coqui🐸 XTTS"
description = """
XTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 3-second audio clip.
Built on Tortoise, XTTS has important model changes that make cross-language voice cloning and multi-lingual speech generation super easy.
This is the same model that powers Coqui Studio, and Coqui API, however we apply a few tricks to make it faster and support streaming inference.
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