File size: 1,280 Bytes
d3912b3 |
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 |
---
license: apache-2.0
tags:
- Hibernates
- HVC-Audio-Convert
pipeline_tag: audio-to-audio
---
# HVC-Audio-Convert Base Models
## Overview
These models serve as the foundational components for HVC-Audio-Convert (Soft-VC Voice Conversion), an advanced voice conversion framework that combines SoftVC feature extraction with the VITS (Conditional Variational Autoencoder with Adversarial Learning) architecture.
## Key Features
- High-quality voice conversion capabilities
- Pre-trained on diverse vocal datasets
- Supports cross-lingual voice conversion
- Compatible with HVC-Audio-Convert v4.0 and newer
## Technical Details
- **Architecture**: Based on VITS (Conditional Variational Autoencoder)
- **Feature Extraction**: Hibernates content encoder
- **Training Data**: Curated multi-speaker datasets
- **Model Format**: PyTorch checkpoints
## Usage
1. Download the desired base model
2. Use with HVC-Audio-Convert framework
3. Fine-tune on target voice data
4. Perform voice conversion
## Requirements
- HVC-Audio-Convert framework
- Python 3.8+
- PyTorch 1.13.0+
- CUDA compatible GPU (recommended)
## License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
## Citation
If you use these models in your research, please cite:
|