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import gradio as gr | |
from transformers import pipeline | |
import numpy as np | |
transcriber = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-arabic") | |
def transcribe(audio): | |
sr, y = audio | |
y = y.astype(np.float32) | |
y /= np.max(np.abs(y)) | |
return transcriber({"sampling_rate": sr, "raw": y})["text"] | |
demo = gr.Interface( | |
transcribe, | |
gr.Audio(sources=["microphone"]), | |
"text", title="S2T: Transcription automatique de l'arabe en text by Papa Séga", | |
description="Utilisez le microphone pour parler en arabe, puis appuyez sur le bouton stop et Submit" | |
) | |
demo.launch(show_error=True, share=True) |