Generating And Protecting Against Adversarial Attacks For Deep Speech-Based Emotion Recognition Models

The development of deep learning models for speech emotion recognition has become a popular area of research. Adversarially generated data can cause false predictions, and in an endeavor to ensure model robustness, defense methods against such attacks sho
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