File size: 2,664 Bytes
bd4c34d e1aa7a1 2dd8e14 bd4c34d 2dd8e14 bd4c34d 2dd8e14 bd4c34d 2dd8e14 bd4c34d 2dd8e14 bd4c34d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
import os
from speechbrain.inference.separation import SepformerSeparation as separator
import torchaudio
import gradio as gr
from moviepy.editor import VideoFileClip
def convert_video_to_audio(video_input):
video_clip = VideoFileClip(video_input)
audio_clip = video_clip.audio
audio_clip_filepath = os.path.normpath(f"{video_input.split('.')[0]}.m4a")
audio_clip.write_audiofile(audio_clip_filepath, codec='aac')
audio_clip.close()
video_clip.close()
return audio_clip_filepath
def speechbrain(input_obj, input_obj_type):
if input_obj_type == "video":
aud = convert_video_to_audio(input_obj)
est_sources = model.separate_file(path=aud)
torchaudio.save("clean_audio_file.wav", est_sources[:, :, 0].detach().cpu(), 8000)
return "clean_audio_file.wav"
def main():
with gr.Blocks(title="Speech Enhancement", delete_cache=(86400, 86400), theme=gr.themes.Base()) as demo:
description = "Gradio demo for Speech Enhancement by 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/2010.13154' target='_blank'>Attention is All You Need in Speech Separation</a> | <a href='https://github.com/speechbrain/speechbrain/tree/develop/templates/enhancement' '_blank'>Github Repo</a></p>"
examples = [
['samples_audio_samples_test_mixture.wav']
]
with gr.Tabs(selected="video") as tabs:
with gr.Tab("Video", id="video"):
gr.Interface(
fn=speechbrain,
inputs=[
gr.Video(type="filepath"),
gr.Radio(choices=["video"], value="video", label="File Type")
]
outputs=[
gr.Audio(label="Output Audio", type="filepath")
],
description=description,
article=article,
examples=examples
)
with gr.Tab("Audio", id="audio"):
gr.Interface(
fn=speechbrain,
inputs=[
gr.Audio(type="filepath"),
gr.Radio(choices=["audio"], value="audio", label="File Type")
]
outputs=[
gr.Audio(label="Output Audio", type="filepath"),
],
description=description,
article=article,
examples=examples
)
demo.launch()
if __name__ == '__main__':
main() |