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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Load the model
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pipe = pipeline("audio-classification", model="dima806/english_accents_classification")
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# Define the inference function
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def classify_accent(audio):
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result = pipe(audio)
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top_result = result[0]
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top3 = "\n".join([f"{r['label']}: {r['score']:.2f}" for r in result[:3]])
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return f"🎤 Top Prediction: {top_result['label']} ({top_result['score']:.2f})\n\nTop 3:\n{top3}"
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# Launch the app
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gr.Interface(
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fn=classify_accent,
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inputs=gr.Audio(type="filepath"),
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outputs=gr.Textbox(),
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title="Accent Classifier 🎧",
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description="Upload an English audio sample to detect the speaker's accent.\nSupported: American, British, Indian, African, Australian.",
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allow_flagging="never"
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).launch()
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