system:
  name: "Res2TCNGuard"
  slug: "res2tcnguard"
  description: >
    TCN-based anti-spoofing countermeasure: sinc-convolution front-end, Res2Net
    encoder, and dual temporal convolutional networks. ASVspoof2019 LA
    pretrained, FP32, deterministic first-64600-sample window (no random crop).
  code: "https://github.com/lab260ru/Res2TCNGuard"
  checkpoint: "https://huggingface.co/SpeechAntiSpoofingBenchmarks/Res2TCNGuard/blob/523ef915d798df3deee2be4fd06af7e1965ede14/best_1.495.pth"
  params_millions: 0.172102
  paper:
    arxiv_id: "10.48084/etasr.8906"
    url: "https://etasr.com/index.php/ETASR/article/view/8906"
    bibtex: |
      @article{Borodin_Kudryavtsev_Mkrtchian_Gorodnichev_2024,
        place={Greece},
        title={Capsule-based and TCN-based Approaches for Spoofing Detection in Voice Biometry},
        volume={14},
        number={6},
        url={https://etasr.com/index.php/ETASR/article/view/8906},
        DOI={10.48084/etasr.8906},
        journal={Engineering, Technology & Applied Science Research},
        author={Borodin, Kirill and Kudryavtsev, Vasiliy and Mkrtchian, Grach and Gorodnichev, Mikhail},
        year={2024},
        month={Dec.},
        pages={18409--18414}
      }
notes: "Deterministic first-64600-sample window (no random crop)."