Audio spoofing detection
Date
2023
Authors
Ivashchenko, Dmytro
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Abstract
Efficient and accurate audio spoofing detection is crucial to ensuring audio-based
systems’ security and integrity. Existing methods often mainly focused on the performance of the detection system. This master thesis focuses on the development of
advanced techniques that prioritize efficiency while maintaining high detection performance. We introduced the model, consisting of an encoder and a classifier, which
can efficiently learn complex representations with a lack of labeled data. We introduce suitable loss functions to effectively distinguish spoofed and bonafide speech
in latent space to keep the performance high. The results demonstrate notable improvements in both encoder performance and classification accuracy, highlighting
the potential for enhanced self-supervised audio analysis techniques.
Keywords: self-supervised learning, audio spoofing detection, automatic speaker
verification, audio processing, speech classification
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Citation
Ivashchenko Dmytro. Audio spoofing detection. Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences. Lviv 2023, 43 p.