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Browse files- README.md +88 -13
- app.py +177 -0
- requirements.txt +8 -0
README.md
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# π€ KittenTTS - High Quality Text-to-Speech
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A Hugging Face Space showcasing the KittenTTS model for high-quality text-to-speech generation.
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## π Features
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- **8 Different Voices**: 4 male and 4 female voices to choose from
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- **High Quality Audio**: 24kHz sample rate for crisp, clear speech
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- **GPU-Free**: Works without requiring a GPU
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- **Easy-to-Use Interface**: Simple and intuitive Gradio web interface
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- **Real-time Generation**: Fast speech synthesis with progress tracking
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## π΅ Available Voices
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| Voice ID | Gender | Description |
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|----------|--------|-------------|
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| `expr-voice-2-m` | Male | Male voice variant 2 |
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| `expr-voice-2-f` | Female | Female voice variant 2 |
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| `expr-voice-3-m` | Male | Male voice variant 3 |
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| `expr-voice-3-f` | Female | Female voice variant 3 |
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| `expr-voice-4-m` | Male | Male voice variant 4 |
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| `expr-voice-4-f` | Female | Female voice variant 4 |
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| `expr-voice-5-m` | Male | Male voice variant 5 |
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| `expr-voice-5-f` | Female | Female voice variant 5 |
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## π οΈ Usage
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1. **Enter Text**: Type or paste your text in the input box
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2. **Select Voice**: Choose from the dropdown menu of available voices
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3. **Generate**: Click the "Generate Speech" button or press Enter
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4. **Download**: Play the generated audio or download it
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## π» Technical Details
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- **Model**: [KittenML/kitten-tts-nano-0.1](https://huggingface.co/KittenML/kitten-tts-nano-0.1)
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- **Sample Rate**: 24kHz
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- **Framework**: KittenTTS
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- **Interface**: Gradio
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- **Audio Format**: WAV (24kHz, mono)
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## π§ Local Development
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To run this locally:
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```bash
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# Clone the repository
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git clone <your-repo-url>
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cd <your-repo-name>
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# Install dependencies
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pip install -r requirements.txt
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# Run the application
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python app.py
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```
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## π¦ Dependencies
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- `gradio>=4.0.0` - Web interface
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- `kittentts` - TTS framework
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- `soundfile` - Audio file handling
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- `numpy` - Numerical operations
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- `torch` - PyTorch backend
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- `torchaudio` - Audio processing
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- `transformers` - Hugging Face transformers
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- `accelerate` - Model acceleration
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## π€ Contributing
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Feel free to contribute by:
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- Reporting bugs
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- Suggesting new features
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- Improving the UI
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- Adding more voice options
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## π License
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This project uses the KittenTTS model. Please refer to the original model's license for usage terms.
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## π Acknowledgments
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- [KittenML](https://huggingface.co/KittenML) for the TTS model
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- [Hugging Face](https://huggingface.co) for the Spaces platform
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- [Gradio](https://gradio.app) for the web interface framework
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---
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**Note**: This is a demonstration of the KittenTTS model. For production use, please ensure compliance with the model's license and terms of use.
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app.py
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import gradio as gr
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import soundfile as sf
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import numpy as np
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from kittentts import KittenTTS
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import os
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# Initialize the model
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model = KittenTTS("KittenML/kitten-tts-nano-0.1")
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# Available voices
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AVAILABLE_VOICES = [
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'expr-voice-2-m', 'expr-voice-2-f', 'expr-voice-3-m', 'expr-voice-3-f',
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'expr-voice-4-m', 'expr-voice-4-f', 'expr-voice-5-m', 'expr-voice-5-f'
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]
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def generate_speech(text, voice, progress=gr.Progress()):
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"""
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Generate speech from text using KittenTTS
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"""
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if not text.strip():
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return None, "Please enter some text to generate speech."
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try:
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progress(0.3, desc="Loading model...")
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# Generate audio
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progress(0.6, desc="Generating speech...")
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audio = model.generate(text, voice=voice)
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progress(0.9, desc="Processing audio...")
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# Convert to the format expected by Gradio
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# Ensure audio is in the correct format (float32, mono)
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if len(audio.shape) > 1:
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audio = audio.mean(axis=1) # Convert stereo to mono if needed
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# Normalize audio
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audio = audio / np.max(np.abs(audio)) if np.max(np.abs(audio)) > 0 else audio
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progress(1.0, desc="Complete!")
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return (24000, audio), f"β
Successfully generated speech with voice: {voice}"
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except Exception as e:
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return None, f"β Error generating speech: {str(e)}"
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def create_demo():
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"""
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Create the Gradio demo interface
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"""
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# Custom CSS for better styling
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css = """
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.gradio-container {
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max-width: 800px !important;
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margin: auto !important;
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}
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.main-header {
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text-align: center;
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margin-bottom: 2rem;
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}
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.voice-selector {
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margin: 1rem 0;
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}
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.output-audio {
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margin-top: 1rem;
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}
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"""
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with gr.Blocks(css=css, title="KittenTTS - High Quality Text-to-Speech") as demo:
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# Header
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gr.HTML("""
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<div class="main-header">
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<h1>π€ KittenTTS</h1>
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<p><em>High Quality Text-to-Speech Generation</em></p>
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<p>Generate natural-sounding speech from text using the KittenTTS model</p>
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</div>
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""")
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with gr.Row():
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with gr.Column(scale=2):
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# Text input
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text_input = gr.Textbox(
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label="Enter your text",
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placeholder="Type or paste your text here...",
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lines=4,
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max_lines=10
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)
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# Voice selection
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voice_dropdown = gr.Dropdown(
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choices=AVAILABLE_VOICES,
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value=AVAILABLE_VOICES[1], # Default to female voice
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label="Select Voice",
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info="Choose from 8 different voices (4 male, 4 female)"
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)
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# Generate button
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generate_btn = gr.Button(
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"π΅ Generate Speech",
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variant="primary",
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size="lg"
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)
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with gr.Column(scale=1):
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# Voice info
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gr.HTML("""
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<div style="background: #f0f0f0; padding: 1rem; border-radius: 8px;">
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<h3>Available Voices:</h3>
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<ul>
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<li><strong>Male voices:</strong> expr-voice-2-m, expr-voice-3-m, expr-voice-4-m, expr-voice-5-m</li>
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<li><strong>Female voices:</strong> expr-voice-2-f, expr-voice-3-f, expr-voice-4-f, expr-voice-5-f</li>
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</ul>
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</div>
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""")
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# Output section
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with gr.Row():
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with gr.Column():
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# Audio output
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audio_output = gr.Audio(
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label="Generated Audio",
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type="numpy",
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sample_rate=24000
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)
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# Status message
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status_output = gr.Textbox(
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label="Status",
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interactive=False
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)
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# Example texts
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gr.Examples(
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examples=[
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["Hello! This is a demonstration of the KittenTTS model.", "expr-voice-2-f"],
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["The quick brown fox jumps over the lazy dog.", "expr-voice-2-m"],
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["Welcome to our high-quality text-to-speech system.", "expr-voice-3-f"],
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["This model works without requiring a GPU.", "expr-voice-3-m"],
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],
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inputs=[text_input, voice_dropdown],
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label="Try these examples:"
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)
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# Footer
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gr.HTML("""
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<div style="text-align: center; margin-top: 2rem; padding: 1rem; background: #f9f9f9; border-radius: 8px;">
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<p><strong>KittenTTS</strong> - Powered by <a href="https://huggingface.co/KittenML/kitten-tts-nano-0.1" target="_blank">KittenML/kitten-tts-nano-0.1</a></p>
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<p>Model: KittenTTS Nano v0.1 | Sample Rate: 24kHz</p>
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</div>
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""")
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# Connect the generate button
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generate_btn.click(
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fn=generate_speech,
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inputs=[text_input, voice_dropdown],
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outputs=[audio_output, status_output]
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)
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# Auto-generate when text is entered and Enter is pressed
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text_input.submit(
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fn=generate_speech,
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inputs=[text_input, voice_dropdown],
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outputs=[audio_output, status_output]
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)
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return demo
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# Create and launch the demo
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if __name__ == "__main__":
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demo = create_demo()
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demo.launch(
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server_name="0.0.0.0",
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server_port=7860,
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share=False
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)
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requirements.txt
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gradio>=4.0.0
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kittentts
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soundfile
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numpy
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torch
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torchaudio
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transformers
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accelerate
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