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Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks


This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in ‘AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks’

Getting started

requirements.txt must be installed for execution. We state our experiment environment for those who prefer to simulate as similar as possible.

pip install -r requirements.txt
  • Our environment (for GPU training)
    • Based on a docker image: pytorch:1.6.0-cuda10.1-cudnn7-runtime
    • GPU: 1 NVIDIA Tesla V100
      • About 16GB is required to train AASIST using a batch size of 24
    • gpu-driver: 418.67

View Github


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Python – Input and Output