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import gradio as gr | |
import ast | |
model = gr.Interface.load("huggingface/pyannote/voice-activity-detection") | |
def format_inference(output): | |
if output: | |
timestamps = [] | |
for out in output: | |
timestamps.append(f"Start: {out['start']}s; Stop: {out['stop']}s") | |
return "\n".join(timestamps) | |
else: | |
return "No voice activity detected." | |
def inference(audio_file): | |
output = model(audio_file) | |
output_list = ast.literal_eval(output) | |
return format_inference(output_list) | |
inputs = gr.inputs.Audio(label="Input Audio", type="filepath", source="upload") | |
outputs = gr.outputs.Textbox(label="Voice timestamps", type="auto") | |
title = "Voice Activity Detection" | |
description = "<p style='text-align: center'>Upload an audio file and detected voices will be timestamped.</p>" | |
article = "<p style='text-align: center'>Model by pyannote, https://github.com/pyannote/pyannote-audio</p>" | |
examples = [["talk.wav"], | |
["talk2.wav"], | |
["silence.wav"],] | |
gr.Interface(inference, | |
inputs, | |
outputs, | |
title=title, | |
description=description, | |
article=article, | |
examples=examples, | |
theme="grass", | |
allow_flagging=False, | |
).launch(debug=True) | |