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---
license: mit
pipeline_tag: audio-to-audio
tags:
- pretrained
- HuBERT
- RVC
- Voice-Conversion
- ai
- vc
- voice-cloning
---
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <style>
        body {
            font-family: Arial, sans-serif;
            padding: 2rem;
            color: #333;
        }
        .container {
            max-width: 800px;
            margin: 0 auto;
            padding: 2rem;
            border-radius: 5px;
            box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
            text-align: center;
        }
        h1 {
            margin-bottom: 1.5rem;
            font-size: 2.5rem;
        }
        h2 {
            margin-bottom: 1rem;
            font-size: 2rem;
        }
        ul {
            list-style: none;
            padding: 0;
            margin: 0;
        }
        ul li {
            margin-bottom: 0.5rem;
        }
        p {
            margin-bottom: 1.5rem;
            font-size: 1.1rem;
        }
        a {
            color: #007bff;
            text-decoration: none;
        }
        a:hover {
            text-decoration: underline;
        }
    </style>
</head>
<body>
    <div class="container">
        <h1>Voice Conversion Hub: Discover Pretrained Models and More</h1>
        <p>Welcome to our comprehensive repository, a treasure trove of pretrained models, HuBERT models, and an assortment of other files and models, all tailored for use in the Retrieval-based Voice Conversion (RVC) neural network.</p>
        <hr style="border: none; height: 2px; background-color: #800080;">
        <h2>Overview</h2>
        <p>This repository is designed to be a one-stop-shop for all your RVC needs. It hosts a wide array of pretrained models, meticulously crafted to provide a robust foundation for your voice conversion tasks. The repository also includes a diverse range of HuBERT models, known for their proficiency in self-supervised speech representation learning.</p>
        <hr style="border: none; height: 2px; background-color: #800080;">
        <h2>Key Features</h2>
        <ul>
            <li><strong>Pretrained Models:</strong> A vast collection of pretrained models, ready to be fine-tuned for your specific voice conversion tasks. These models have been trained on diverse datasets, ensuring a broad spectrum of voice characteristics.</li>
            <li><strong>HuBERT Models:</strong> A selection of HuBERT models, recognized for their ability to learn high-quality speech representations from raw audio data. These models are ideal for tasks that require a deep understanding of speech nuances.</li>
            <li><strong>Additional Files and Models:</strong> A miscellaneous collection of files and models that can be beneficial for various aspects of voice conversion, from data preprocessing to model evaluation.</li>
        </ul>
        <hr style="border: none; height: 2px; background-color: #800080;">
        <p>We invite you to explore this repository, leverage its resources, and contribute to the advancement of voice conversion technology. Whether you're a seasoned researcher or a budding enthusiast, we believe you'll find something of value here.</p>
        <p>Happy exploring, and let's shape the future of voice conversion together!</p>
    </div>
</body>
</html>