# Spoof Detection on ASVspoof 2021 (test) Source: [Spoof Detection on ASVspoof 2021 (test)]() Collection index: [llms.txt]() Data updated: 2026-06-16T10:52:41.245Z Evaluation of spoof detection performance using the test set of the ASVspoof 2021 dataset, reporting metrics including AUC and EER. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Spoof Detection | | Dataset (including any stated split) | ASVspoof 2021 (test) | | Metric | AUC | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 1 of 1 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [AUC](): Higher is better; unit: PERCENT. - [EER](): Lower is better; unit: PERCENT. ## Recorded results | Method | AUC | Result date | Report paper | | --- | --- | --- | --- | | XLS-SLS (Pyramid) | 82.99 | Not recorded | 6a30d91bd33dfb23e783d2ae | ### XLS-SLS (Pyramid) AUC: 82.99. Result ID: 6a312adffbc373592c2e6ba6. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Training Dataset":"DiffSSD"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.