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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")
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 = """
<a href="https://huggingface.co/coqui/XTTS-v1">XTTS</a> is a Voice generation model that lets you clone voices into different languages by using just a quick 3-second audio clip.
<br/>
Built on Tortoise, XTTS has important model changes that make cross-language voice cloning and multi-lingual speech generation super easy.
<br/>
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.
<br/>
<br/>
<p>For faster inference without waiting in the queue, you should duplicate this space and upgrade to GPU via the settings.
<br/>
<a href="https://huggingface.co/spaces/coqui/xtts?duplicate=true">
<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
</p>
"""
article = """
<div style='margin:20px auto;'>
<p>By using this demo you agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml</p>
</div>
"""
examples = [
[
"Once when I was six years old I saw a magnificent picture",
"en",
"examples/female.wav",
None,
False,
True,
],
[
"Lorsque j'avais six ans j'ai vu, une fois, une magnifique image",
"fr",
"examples/male.wav",
None,
False,
True,
],
[
"Un tempo lontano, quando avevo sei anni, vidi un magnifico disegno",
"it",
"examples/female.wav",
None,
False,
True,
],
[
"Bir zamanlar, altı yaşındayken, muhteşem bir resim gördüm",
"tr",
"examples/female.wav",
None,
False,
True,
],
]
gr.Interface(
fn=predict,
inputs=[
gr.Textbox(
label="Text Prompt",
info="One or two sentences at a time is better",
value="It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.",
),
gr.Dropdown(
label="Language",
info="Select an output language for the synthesised speech",
choices=[
"en",
"es",
"fr",
"de",
"it",
"pt",
"pl",
"tr",
"ru",
"nl",
"cz",
"ar",
"zh-cn",
],
max_choices=1,
value="en",
),
gr.Audio(
label="Reference Audio",
info="Click on the ✎ button to upload your own target speaker audio",
type="filepath",
value="examples/female.wav",
),
gr.Audio(source="microphone",
type="filepath",
info="Use your microphone to record audio",
label="Use Microphone for Reference"),
gr.Checkbox(label="Check to use Microphone as Reference", value=False),
gr.Checkbox(
label="Agree",
value=False,
info="I agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml",
),
],
outputs=[
gr.Video(label="Waveform Visual"),
gr.Audio(label="Synthesised Audio"),
],
title=title,
description=description,
article=article,
examples=examples,
).queue().launch(debug=True)