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import gradio as gr |
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from transformers import pipeline |
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import torch |
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import torchaudio |
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ar") |
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tts_model = pipeline("text-to-speech", model="microsoft/speecht5_tts") |
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def translate_and_speak(text, lang): |
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if lang == "English → Arabic": |
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translation = translator(text, max_length=200)[0]['translation_text'] |
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else: |
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translation = translator(text, max_length=200, src_lang="ar", tgt_lang="en")[0]['translation_text'] |
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tts_audio = tts_model(translation) |
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return translation, (tts_audio["sampling_rate"], tts_audio["audio"]) |
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iface = gr.Interface( |
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fn=translate_and_speak, |
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inputs=[ |
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gr.Textbox(label="أدخل النص"), |
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gr.Radio(["English → Arabic", "Arabic → English"], label="اتجاه الترجمة"), |
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], |
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outputs=[ |
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gr.Textbox(label="النص المترجم"), |
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gr.Audio(label="النص المنطوق"), |
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], |
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title="مترجم ونطق النصوص", |
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description="هذا النموذج يترجم النصوص بين العربية والإنجليزية ثم يحولها إلى صوت." |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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