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import gradio as gr
title = "FastSpeech2"
description = "Gradio Demo for fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.06912' target='_blank'>fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit</a> | <a href='https://github.com/pytorch/fairseq/tree/main/examples/speech_synthesis' target='_blank'>Github Repo</a></p>"
examples = [
["Hello, this is a test run.","fastspeech2-en-200_speaker-cv4"]
]
io1 = gr.Interface.load("huggingface/facebook/fastspeech2-en-200_speaker-cv4")
io2 = gr.Interface.load("huggingface/facebook/fastspeech2-en-ljspeech")
def inference(text, model):
if model == "fastspeech2-en-200_speaker-cv4":
audio = io1(text)
else:
audio = io2(text)
return audio
gr.Interface(
inference,
[gr.inputs.Textbox(label="Input", lines=10),gr.inputs.Dropdown(choices=["fastspeech2-en-200_speaker-cv4","fastspeech2-en-ljspeech"], type="value", default="prophetnet-large-uncased", label="model")
],
gr.outputs.Audio(label="Output"),
examples=examples,
article=article,
title=title,
description=description).launch(enable_queue=True, cache_examples=True)
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