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import gradio as gr |
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import whisper |
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def speech_to_text(uploaded, model_size): |
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model = whisper.load_model(model_size) |
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source = uploaded if uploaded is not None else '' |
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result = model.transcribe(source) |
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return f'{result["text"]}' |
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gr.Interface( |
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title="", |
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thumbnail="", |
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css=""" |
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footer {visibility: xhidden} |
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.gr-prose p{text-align: center;} |
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.gr-button {background: black;color: white} |
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""", |
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description="", |
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fn=speech_to_text, |
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inputs=[ |
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gr.Audio(source="upload", type="filepath", label="Upload Audio"), |
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gr.Dropdown(label="Select model size",value="large",choices=["tiny", "base", "small", "medium", "large"])], |
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outputs="text").launch(debug = True) |
