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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="kotoba-tech/kotoba-whisper-v1.0") |
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def transcribe(stream, new_chunk): |
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sr, y = new_chunk |
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y = y.astype(np.float32) |
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y /= np.max(np.abs(y)) |
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if stream is not None: |
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stream = np.concatenate([stream, y]) |
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else: |
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stream = y |
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return stream, transcriber({"sampling_rate": sr, "raw": stream})["text"] |
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demo = gr.Interface( |
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transcribe, |
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["state", gr.Audio(sources=["microphone"], streaming=True)], |
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["state", "text"], |
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live=True, |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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