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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) |