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app.py
Browse files- app.py +20 -0
- flagged/audio/3078fa84e061327e99b6/audio.wav +0 -0
- flagged/log.csv +2 -0
app.py
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from transformers import pipeline
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import gradio as gr
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pipe = pipeline(model="asif00/whisper-bangla")
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def transcribe(audio):
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text = pipe(audio)["text"]
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return text
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iface = gr.Interface(
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fn=transcribe,
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inputs=gr.Audio(sources="microphone", type="filepath"),
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outputs="text",
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title="Whisper Bangla",
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description="Realtime demo for Bengali speech recognition using a fine-tuned Whisper small model.",
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)
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iface.launch()
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flagged/audio/3078fa84e061327e99b6/audio.wav
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Binary file (307 kB). View file
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flagged/log.csv
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audio,output,flag,username,timestamp
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flagged\audio\3078fa84e061327e99b6\audio.wav,আফনি কেমন আসেন।,,,2024-06-04 01:02:36.210092
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