--- license: mit pipeline_tag: audio-to-audio tags: - pretrained - HuBERT - RVC - Voice-Conversion - ai - vc - voice-cloning ---

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.

Overview

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.

Key Features

Pretrained Models: 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.
HuBERT Models: 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.
Additional Files and Models: A miscellaneous collection of files and models that can be beneficial for various aspects of voice conversion, from data preprocessing to model evaluation.

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.

Happy exploring, and let's shape the future of voice conversion together!