This repo provides codes for our ICASSP 2023 paper "SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing".
- Installing dependencies
pip install -r requirements.txt
- Running environment
- 1 GPU: GeForce GTX 1080 Ti
- ~11GB required for a batch size of 23
- Dataset for train/val/eval:
- Download ASVspoof 2019 logical access dataset here
- Specify path to the 'LA' folder in argument
--path_to_database
The main.py file contains train/val/eval steps for Softmax/OC-Softmax/SAMO.
For example, to train SAMO:
python3 samo/main.py -o 'path_to_output_folder' -d 'path_to_database' -p 'path_to_protocol' --overwrite
Please check argument setups in main.py to specify settings such as batch size and margins.
To evaluate pretrained SAMO:
python3 samo/main.py --test_only --test_model "./models/samo.pt" --scoring 'samo' --save_score "samo_score"
And the output will show Test EER: 0.008751418248624953
This is built upon open-source repos:
@inproceedings{ding2023samo,
title={SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing},
author={Ding, Siwen and Zhang, You and Duan, Zhiyao},
booktitle={Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year={2023}
}@article{wang2020asvspoof,
title={ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech},
author={Wang, Xin and Yamagishi, Junichi and Todisco, Massimiliano and Delgado, H{\'e}ctor and Nautsch, Andreas and Evans, Nicholas and Sahidullah, Md and Vestman, Ville and Kinnunen, Tomi and Lee, Kong Aik and others},
journal={Computer Speech \& Language},
volume={64},
pages={101114},
year={2020},
publisher={Elsevier}
}@ARTICLE{zhang21one,
author={Zhang, You and Jiang, Fei and Duan, Zhiyao},
journal={IEEE Signal Processing Letters},
title={One-Class Learning Towards Synthetic Voice Spoofing Detection},
year={2021},
volume={28},
number={},
pages={937-941},
doi={10.1109/LSP.2021.3076358}}@INPROCEEDINGS{Jung2021AASIST,
author={Jung, Jee-weon and Heo, Hee-Soo and Tak, Hemlata and Shim, Hye-jin and Chung, Joon Son and Lee, Bong-Jin and Yu, Ha-Jin and Evans, Nicholas},
booktitle={arXiv preprint arXiv:2110.01200},
title={AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks},
year={2021}