Modern Voice Authentication Systems

Student: Bekyan Artyom

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2024

As deep learning develops, bypassing voice authentication systems becomes easier. One of the significant problems is connected with the great variety of possible attacks, making Out-Of-Domain (OOD) generalization crucial. This paper proposes a novel framework that achieves this goal by using multi-task learning. Unlike the previous approach, our framework applies to the models that use raw waveform as the front-end. The experimental results show that it can significantly improve the model prediction quality.

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