---
license: apache-2.0
language:
- en
tags:
- ai
- rvc
- vc
- voice-cloning
- applio
- titan
- pretrained
datasets:
- blaise-tk/TITAN-Medium
pipeline_tag: audio-to-audio
---
# TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training

## Overview
TITAN is a state-of-the-art pretrained model designed for Retrieval-based Voice Conversion (https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/) training. It offers a robust solution for transforming voice characteristics from one speaker to another, providing high-quality results with minimal training effort.

## Model Details
### Titan-Medium
- Training Environment: Utilized a RTX 3060 TI on Applio v3.1.1 (https://github.com/IAHispano/Applio), employing a batch size of 8 over a span of 3 weeks.
- Iterations: X Steps
- Epochs: X
- Sampling rate: 40k, 32k (still training)
- Fine-tuning Process: RVC v2 pretrained with pitch guidance, leveraging an 11.15-hour dataset sourced from Expresso (https://arxiv.org/abs/2308.05725) also available on [datasets/blaise-tk/TITAN-Medium](https://huggingface.co/datasets/blaise-tk/TITAN-Medium).

### Titan-Large
- Details forthcoming...

## Collaborators
We appreciate the contributions of our collaborators who have helped in the development and refinement of TITAN.

- Mustar
- SimplCup

## Beta Testers
We extend our gratitude to the beta testers who provided valuable feedback during the testing phase of TITAN.

- SimplCup
- Leo_Frixi
- Light
- SCRFilms

## Citation
Should you find TITAN beneficial for your research endeavors or projects, we kindly request citing our repository:

```
@article{titan,
  title={TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training},
  author={Blaise},
  journal={Hugging Face},
  year={2024},
  publisher={Blaise},
  url={https://huggingface.co/blaise-tk/TITAN/}
}
```