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import torch | |
import torchaudio | |
from speechbrain.pretrained import SpectralMaskEnhancement | |
import gradio as gr | |
enhance_model = SpectralMaskEnhancement.from_hparams( | |
source="speechbrain/metricgan-plus-voicebank", | |
savedir="pretrained_models/metricgan-plus-voicebank", | |
) | |
def speechbrain(aud): | |
# Load and add fake batch dimension | |
noisy = enhance_model.load_audio( | |
aud | |
).unsqueeze(0) | |
enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.])) | |
torchaudio.save('enhanced.wav', enhanced.cpu(), 16000) | |
return 'enhanced.wav' | |
inputs = gr.Audio(label="Input Audio", type="filepath") | |
outputs = gr.Audio(label="Output Audio", type="filepath") | |
title = "Speechbrain Speech Enhancement" | |
description = "Gradio demo for Speech enhancement with SpeechBrain. To use it, simply upload 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/2104.03538' target='_blank'>MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement</a> | <a href='https://github.com/speechbrain/speechbrain' target='_blank'>Github Repo</a></p>" | |
examples = [ | |
['samples_audio_samples_example_fr.wav'] | |
] | |
gr.Interface(speechbrain, inputs, outputs, title=title, description=description, article=article, examples=examples).launch() |