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---
language:
- "en"
thumbnail:
tags:
- audio-to-audio
- Speech Enhancement
- Voicebank-DEMAND
- UNIVERSE
- UNIVERSE++
- Diffusion
- pytorch
- open-universe
license: "apache-2.0"
datasets:
- Voicebank-DEMAND
metrics:
- SI-SNR
- PESQ
- SIG
- BAK
- OVRL
model-index:
- name: universe++
results:
- task:
name: Speech Enhancement
type: speech-enhancement
dataset:
name: Voicebank-DEMAND
type: demand
split: test-set
args:
language: en
metrics:
- name: DNSMOS SIG
type: sig
value: '3.493'
- name: DNSMOS BAK
type: bak
value: '4.042'
- name: DNSMOS OVRL
type: ovrl
value: '3.205'
- name: PESQ
type: pesq
value: 3.017
- name: SI-SDR
type: si-sdr
value: 18.629
---
# Open-UNIVERSE: Generative Speech Enhancement with Score-based Diffusion and Adversarial Training
This repository contains the configurations and weights for the [UNIVERSE++](tba) and
[UNIVERSE](https://arxiv.org/abs/2206.03065) models implemented in [open-universe](https://github.com/line/open-universe).
The models were trained on the [Voicebank-DEMAND](https://datashare.ed.ac.uk/handle/10283/2791) dataset at 16 kHz.
The performance on the test split of Voicebank-DEMAND is given in the following table.
| model | si-sdr | pesq-wb | stoi-ext | lsd | lps | OVRL | SIG | BAK |
|------------|----------|-----------|------------|-------|-------|--------|-------|-------|
| UNIVERSE++ | 18.629 | 3.017 | 0.865 | 4.868 | 0.937 | 3.205 | 3.493 | 4.042 |
| UNIVERSE | 17.594 | 2.834 | 0.845 | 6.318 | 0.920 | 3.156 | 3.455 | 4.013 |
## Usage
Start by installing `open-universe`.
We use conda to simplify the installation.
```sh
git clone https://github.com/line/open-universe.git
cd open-universe
conda env create -f environment.yaml
conda activate open-universe
python -m pip install .
```
Then the models can be used as follows.
```sh
# UNIVERSE++ (default model)
python -m open_universe.bin.enhance <input/folder> <output/folder> \
--model line-corporation/open-universe:plusplus
# UNIVERSE
python -m open_universe.bin.enhance <input/folder> <output/folder> \
--model line-corporation/open-universe:original
```
## Referencing open-universe and UNIVERSE++
If you use these models in your work, please consider citing the following paper.
```latex
@inproceedings{universepp,
authors={Scheibler, Robin and Fujita, Yusuke and Shirahata, Yuma and Komatsu, Tatsuya},
title={Universal Score-based Speech Enhancement with High Content Preservation},
booktitle={Proc. Interspeech 2024},
month=sep,
year=2024
}
```
## Referencing UNIVERSE
```latex
@misc{universe,
authors={Serr\'a, Joan and Santiago, Pascual and Pons, Jordi and Araz, Oguz R. and Scaini, David},
title={Universal Speech Enhancement with Score-based Diffusion},
howpublished={arXiv:2206.03065},
month=sep,
year=2022
}
```
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