Explainable AI in Speaker Recognition -- Making Latent Representations Understandable 事件

Explainable AI in Speaker Recognition -- Making Latent Representations Understandable arXiv:2604.23354v2 Announce Type: replace-cross Abstract: Neural networks can be trained to learn task-relevant representations from data. Understanding how these networks make decisions falls within the Explainable AI (XAI) domain. This paper proposes to study an XAI topic: uncovering the unknown organisation in the representations, particularly those a speaker recognition network learns from utterances, for