SIGMA applies post-hoc XAI saliency maps to define reusable sparse masks for magnitude-bounded perturbations on self-supervised speech features, evaluated on IEMOCAP and TESS for competitive attack success with explanation consistency trade-offs.
Ex- HuBERT: Enhancing HuBERT through block extension and fine-tuning on 37 emotion datasets,
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SIGMA: Saliency-Guided Sparse Mask Attacks for Speech Emotion Recognition
SIGMA applies post-hoc XAI saliency maps to define reusable sparse masks for magnitude-bounded perturbations on self-supervised speech features, evaluated on IEMOCAP and TESS for competitive attack success with explanation consistency trade-offs.