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Create app.py
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app.py
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import gradio as gr
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import tensorflow as tf
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import numpy as np
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import soundfile as sf
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import os
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MODEL_PATH = "model/clone_tts_model.h5"
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TEXT_MAX_LEN = 100
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SAMPLE_RATE = 22050
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# Load model once
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model = tf.keras.models.load_model(MODEL_PATH)
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def synthesize(text):
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x_input = np.array([[ord(c) for c in text.ljust(TEXT_MAX_LEN)[:TEXT_MAX_LEN]]])
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audio = model.predict(x_input)[0]
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output_path = "output/generated.wav"
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os.makedirs("output", exist_ok=True)
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sf.write(output_path, audio, SAMPLE_RATE)
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return output_path
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demo = gr.Interface(
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fn=synthesize,
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inputs=gr.Textbox(label="Enter Text"),
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outputs=gr.Audio(label="Generated Speech", type="filepath"),
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title="Clone TTS",
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description="A simple Text-to-Speech model trained on the 'clone' dataset."
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)
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if __name__ == "__main__":
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demo.launch()
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