Voice authentication has evolved from traditional systems based on hand-engineered acoustic features to deep learning models that learn speaker representations directly from audio. This progress has improved accuracy, but it has also opened new attack surfaces. Prior surveys treat these threats in isolation; we inste...
Speaker verification systems encounter combinations of noise, channel distortion, and changes in speech. Evaluating each condition separately does not establish whether their effects add. InterBias-SV organises this question around a four-term comparison: joint error, two marginal errors, and a common reference. Its re...
A comprehensive review of the modern threat landscape targeting Voice Authentication Systems (VAS) and Anti-Spoofing Countermeasures (CMs), including data poisoning, adversarial, deepfake, and adversarial spoofing attacks is presented.
