Comparison of state-of-the-art deep learning models for audio deepfakes detection in the context of audio DeepFakes across 8 languages (English, German, Polish, Ukrainian, Russian, Spanish, French, Italian).
The system joins keylogger and text editor functionalities to gather data. Features describing each user are extracted using natural language processing techniques and metrics.
Proposal of an effective feature selection method to reduce the vulnerability of a machine learning system to a backdoor attack.
Comparison of different spell checkers in Python in terms of their effectiveness in detecting typos (randomly generated, QWERTY-based).