File size: 3,139 Bytes
297935a 2b045bc 297935a 2b045bc cdcddfb 2b045bc 297935a 2b045bc 297935a 2b045bc 297935a 2b045bc 297935a 2b045bc cdcddfb 297935a 2b045bc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: mit
pipeline_tag: audio-to-audio
tags:
- pretrained
- HuBERT
- RVC
- Voice Conversion
---
<!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>
<title>Model Card for RVC-HuBERT</title>
</head>
<body>
<div class="container">
<h1>Model Card for RVC-HuBERT</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>
<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>
<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>
<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>
|