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Exploring a Behavioral Model of "Positive Friction" in Human-AI Interaction
Designing seamless, frictionless user experiences has long been a dominant trend in both applied behavioral science and artificial intelligence (AI), in which the goal of making desirable actions easy and efficient informs efforts to minimize friction in user experiences.
Adversarial Reweighting for Speaker Verification Fairness
Results show that the pairwise weighting method can achieve 1. 08% overall EER, 1. 25% for male and 0. 67% for female speakers, with relative EER reductions of 7. 7%, 10. 1% and 3. 0%, respectively.
Self-supervised Speaker Recognition Training Using Human-Machine Dialogues
Speaker recognition, recognizing speaker identities based on voice alone, enables important downstream applications, such as personalization and authentication.
Fusion of Embeddings Networks for Robust Combination of Text Dependent and Independent Speaker Recognition
Based on whether the speech content is constrained or not, both text-dependent (TD) and text-independent (TI) speaker recognition models may be used.
