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This paper describes our submitted systems to the 2022 ADD challenge withingthe tracks 1 and 2. Our approach is based on the combination of a pre-trainedwav2vec2 feature extractor and a downstream classifier to detect spoofed audio.This method exploits the contextualized speech representations at the differenttransformer layers to fully capture discriminative information. Furthermore,the classification model is adapted to the application scenario using differentdata augmentation techniques. We evaluate our system for audio synthesisdetection in both the ASVspoof 2021 and the 2022 ADD challenges, showing itsrobustness and good performance in realistic challenging environments such astelephonic and audio codec systems, noisy audio, and partial deepfakes.

The Vicomtech Audio Deepfake Detection System based on Wav2Vec2 for the 2022 ADD Challenge