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import gradio as gr | |
import torch | |
from transformers import pipeline | |
canary_pipe = pipeline("automatic-speech-recognition", model="nvidia/canary-1b") | |
def convert_speech(audio): | |
sr, y = audio | |
y = y.astype(np.float32) | |
y /= np.max(np.abs(y)) | |
return transcriber({"sampling_rate": sr, "raw": y})["text"] | |
iface = gr.Interface(fn=convert_speech, inputs=gr.Audio(sources="microphone"), outputs="textbox") | |
iface.launch() |