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| import gradio as gr | |
| from transformers import pipeline | |
| import numpy as np | |
| def recognize_speech(audio): | |
| print (type(audio)) | |
| transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en") | |
| sr, y = audio | |
| y = y.astype(np.float32) | |
| y /= np.max(np.abs(y)) | |
| return transcriber({"sampling_rate": sr, "raw": y})["text"] | |
| gr.close_all() | |
| demo = gr.Interface(fn=recognize_speech, inputs="audio", outputs="text") | |
| demo.launch() |