README.md

---
license: mit
language:
- ja
metrics:
- accuracy
pipeline_tag: text-to-speech
tags:
- rvc
library_name: fairseq
---

# Its not my model!

# <center> RVC Genshin Impact Japanese Voice Model
![model-cover.png](https://huggingface.co/ArkanDash/rvc-genshin-impact/resolve/main/model-cover.png)

## About Retrieval based Voice Conversion (RVC)
Learn more about Retrieval based Voice Conversion in this link below:
[RVC WebUI](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)

## How to use? 
Download the prezipped model and put to your RVC Project.

Model test: [Google Colab](https://colab.research.google.com/drive/110kiMZTdP6Ri1lY9-NbQf17GVPPhHyeT?usp=sharing) / [RVC Models New](https://huggingface.co/spaces/ArkanDash/rvc-models-new) (Which is basically the same but hosted on spaces)

## <center> INFO
Model Created by ArkanDash<br />
The voice that was used in this model belongs to Hoyoverse.<br />
The voice I make to make this model was ripped from the game (3.6 - 4.0). 
#### Total Models: 46 Models
V1 Models: 19 <br />
V2 Models: 27

Duplicate:
- Zhongli (v1 & v2)
- Nahida (v1 & v2)

Plans:
- Character from fontaine.
- v2 model recreation from v1 model.

Note:
- For faruzan, somehow the index file is smaller, Might retrain faruzan.
Error message: `Converged (lack of improvement in inertia) at step 1152/48215` <br />
- Furina has only 20 minutes of dataset. (Will update the model in the future when its 1 hour long)
- New model will be created using v2 training, I'm no longer making v1 model.

Have a request?<br />
I accept genshin character request if you want it.
Other request outside playable character:<br />
- Greater Lord Rukkhadevata: 750 Epochs, 16 Batch size, 48k Sample rate. (10 minutes dataset)
- Charlotte: 400 Epochs, 16 Batch size, 48k Sample rate. (18 minutes dataset)
- La Signora 1k Epochs, 16 Batch size, 48k Sample rate. (8 minutes dataset)

## <center> Model Training Information

### V1 Model Training <br />
##### This was trained on Original RVC.
Pitch Extract using Harvest.<br />
This model was trained with 100 epochs, 10 batch sizes, and a 40K sample rate (some models had a 48k sample rate).

Every V1 model was trained more or less around 30 minutes of character voice.

### V2 Model Training <br />
##### This was trained on Mangio-Fork RVC.
Pitch Extract using Crepe.<br />
This model was trained with 100 epochs, 8 batch sizes, and a 48K sample rate. (some models had a 40k sample rate).

Every V2 model was trained more or less around 60 minutes of character voice.

## Warning
I'm not responsible for the output of this model.
Use wisely.