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import os | |
os.system('pip install gradio==2.3.0a0') | |
os.system('pip freeze') | |
from voicefixer import VoiceFixer | |
import gradio as gr | |
voicefixer = VoiceFixer() | |
def inference(audio,mode): | |
voicefixer.restore(input=audio.name, # input wav file path | |
output="output.wav", # output wav file path | |
cuda=False, # whether to use gpu acceleration | |
mode = int(mode)) # You can try out mode 0, 1 to find out the best result | |
return 'output.wav' | |
inputs = [gr.inputs.Audio(type="file", label="Input Audio"),gr.inputs.Radio(choices=['0','1','2'], type="value", default='0', label='mode')] | |
outputs = gr.outputs.Audio(type="file",label="Output Audio") | |
title = "Voice Fixer" | |
description = "Gradio demo for VoiceFixer: Toward General Speech Restoration With Neural Vocoder. To use it, simply add your audio, 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/2109.13731' target='_blank'>VoiceFixer: Toward General Speech Restoration With Neural Vocoder</a> | <a href='https://github.com/haoheliu/voicefixer_main' target='_blank'>Github Repo</a></p>" | |
examples=[['bruce.wav','2']] | |
gr.Interface(inference, inputs, outputs, title=title, description=description, article=article, examples=examples, enable_queue=True).launch() |