Upload gr_iabd.py
Browse files- gr_iabd.py +25 -0
gr_iabd.py
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import torch
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from transformers import pipeline
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import numpy as np
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import gradio as gr
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pipe = pipeline(
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"automatic-speech-recognition", model="openai/whisper-base"
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)
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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 pipe({"sampling_rate": sr, "raw": y})["text"]
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demo = gr.Interface(
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transcribe,
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gr.Audio(sources=["microphone"]),
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"text",
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)
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demo.launch()
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