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| 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): | |
| model = separator.from_hparams(source="speechbrain/sepformer-whamr-enhancement", savedir='pretrained_models/sepformer-whamr-enhancement') | |
| if input_obj_type == "video": | |
| aud = convert_video_to_audio(input_obj) | |
| else: | |
| aud = 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.Ocean()) as demo: | |
| gr.Markdown("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.") | |
| gr.Markdown("<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(), | |
| gr.Radio(choices=["video"], value="video", label="File Type") | |
| ], | |
| outputs= [ | |
| gr.Audio(label="Output Audio", type="filepath") | |
| ] | |
| ) | |
| 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") | |
| ] | |
| ) | |
| demo.launch() | |
| if __name__ == '__main__': | |
| main() |