Update app.py
Browse files
app.py
CHANGED
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import gradio as gr
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from transformers import FastSpeechForConditionalGeneration, Wav2Vec2Processor
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# تحميل
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model = FastSpeechForConditionalGeneration.from_pretrained("facebook/fastspeech2-en-ljspeech")
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processor = Wav2Vec2Processor.from_pretrained("facebook/fastspeech2-en-ljspeech")
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def tts(text):
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inputs = processor(text, return_tensors="pt")
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speech = model.generate(**inputs)
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return processor.decode(speech[0])
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# واجهة Gradio
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iface = gr.Interface(fn=tts, inputs="text", outputs="audio", title="
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iface.launch()
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import gradio as gr
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from transformers import FastSpeechForConditionalGeneration, Wav2Vec2Processor, AutoTokenizer, AutoModel
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# تحميل نموذج SaudiBERT لتحليل النص
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tokenizer = AutoTokenizer.from_pretrained("faisalq/SaudiBERT")
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bert_model = AutoModel.from_pretrained("faisalq/SaudiBERT")
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# تحميل نموذج FastSpeech
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model = FastSpeechForConditionalGeneration.from_pretrained("facebook/fastspeech2-en-ljspeech")
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processor = Wav2Vec2Processor.from_pretrained("facebook/fastspeech2-en-ljspeech")
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# دالة لتحليل النص باستخدام SaudiBERT
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def analyze_text_with_bert(text):
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inputs = tokenizer(text, return_tensors="pt")
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outputs = bert_model(**inputs)
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return outputs
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# دالة تحويل النص إلى كلام
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def tts(text):
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# تحليل النص قبل التحويل باستخدام SaudiBERT
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analyzed_text = analyze_text_with_bert(text)
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inputs = processor(text, return_tensors="pt")
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speech = model.generate(**inputs)
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return processor.decode(speech[0])
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# واجهة Gradio
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iface = gr.Interface(fn=tts, inputs="text", outputs="audio", title="Najdi TTS with SaudiBERT")
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iface.launch()
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