---
# System prepended metadata

title: BIIC x C-Media Report (Voice Conversion)
tags: [Internship, Machine Learning]

---

# BIIC x C-Media Report (Voice Conversion)
###### tags: `Internship`,`Machine Learning`
###### Date: 202207
[TOC]
## Problem Definition : Voice Conversion Deep Learning Modeling
![](https://i.imgur.com/be3M4r1.png)
![](https://i.imgur.com/yV4YGEy.png)
## Datasets
![](https://i.imgur.com/wVY3TmU.png)
![](https://i.imgur.com/Nl1J3kR.png)
## Methodology
### Overview
1. Autoencoder
• Ada-VC:
Chou, Ju-chieh, Cheng-chieh Yeh, and Hung-yi Lee. "One-shot voice conversion by separating speaker and content representations with instance normalization." arXiv preprint arXiv:1904.05742 (2019).
• FragmentVC:
Lin, Yist Y., et al. "Fragmentvc: Any-to-any voice conversion by end-to-end extracting and fusing fine-grained voice fragments with attention." ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021.
2. StarGAN
• StarGAN-VC:
Kameoka, Hirokazu, et al. "Stargan-vc: Non-parallel many-to-many voice conversion using star generative adversarial networks." 2018 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2018.
• StarGAN-VC-2
Kaneko, Takuhiro, et al. "StarGAN-VC2: Rethinking conditional methods for StarGAN-based voice conversion." arXiv preprint arXiv:1907.12279 (2019).
### Autoencoder – Ada-VC
![](https://i.imgur.com/H8y9gA1.png)
![](https://i.imgur.com/PqHf5em.png)
### StarGAN – VC
![](https://i.imgur.com/4WYqAcN.png)
![](https://i.imgur.com/oe2KonH.png)
![](https://i.imgur.com/Bm61rzY.png)
### StarGAN – VC2
![](https://i.imgur.com/WutGmP9.png)
![](https://i.imgur.com/iQbpw78.png)
![](https://i.imgur.com/gDbjIdB.png)
![](https://i.imgur.com/WRjJR4B.png)
![](https://i.imgur.com/HJDs00U.png)

#### Cold down mechanism 
![](https://i.imgur.com/oKOpCiY.png)
## Evaluation metrics
MOS, speaker embedding cosine similarity
![](https://i.imgur.com/c40Ghqp.png)
### Mean Opinion Score
![](https://i.imgur.com/pVpjZTY.png)
![](https://i.imgur.com/zV0C5xi.png)
![](https://i.imgur.com/aZVNLj0.png)
### Speaker embedding cosine similarity
![](https://i.imgur.com/vevJSB1.png)
![](https://i.imgur.com/0I4xdVP.png)
![](https://i.imgur.com/0CEuQ7s.png)
## Experiment Setup
![](https://i.imgur.com/LOqA7V5.png)
## Result
![](https://i.imgur.com/LrvzSlD.png)
![](https://i.imgur.com/iGEd87K.png)


















