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caa3c0d
Create asr_transcription.ipynb
Browse files- asr_transcription.ipynb +21 -0
asr_transcription.ipynb
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import gradio as gr
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from transformers import pipeline
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import numpy as np
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transcriber = pipeline('automatic-speech-recognition', model='openai/whisper-base')
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def transcribe(audio):
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sr, y = audio
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y = y.astype(np.float32)
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y /= np.max(np.abs(y))
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return transcriber({'sampling_rate': sr, 'raw': y})['text']
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demo = gr.Interface(
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fn = transcribe,
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inputs = gr.Audio(sources=['microphone']),
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outputs = 'text',
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)
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demo.launch()
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