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# System prepended metadata

title: SASV Challenge 2022

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# SASV Challenge 2022
- https://arxiv.org/pdf/2201.10283.pdf
- https://sasv-challenge.github.io/
- https://github.com/sasv-challenge/SASVC2022_Baseline

## Idea
- Use the three embeddings (enroll embedding A, testing embedding B, cm embedding C) as query, key and values (using 2 transformers, one take A, B, C as query, key, value, and the other take A, B, C as query, value, key) to train a scoring model

## reference
### https://arxiv.org/pdf/2006.05599.pdf
![](https://i.imgur.com/3dbdD6D.png)
- use the anti-spoofing label to help asv training


### https://arxiv.org/pdf/2202.05253.pdf
![](https://i.imgur.com/u4nN8ef.png)
![](https://i.imgur.com/AEB2K5R.png)
- use asv score to help the anti-spoofing layer training. Large asv score with result in large gradient (if the trial is spoofing, then it will benefit from the large gradient).

## Experiments
