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* changes * changes * revert changes * changes * add changeset * notebooks script * changes * changes --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Ali Abdalla <ali.si3luwa@gmail.com>
27 lines
659 B
Python
27 lines
659 B
Python
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.en")
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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"] # type: ignore
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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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