Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices

Abstract

This study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the Deep Speaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by altering medical records, causing inaccurate diagnoses and treatments. In banking, they threaten biometric security, increasing the risk of financial fraud and identity theft. The research reveals the neural network's superiority over human detection in pinpointing cloned voices, underscoring the urgent need for sophisticated AI-based security. The study stresses the importance of developing robust defenses against voice cloning attacks, which can have critical consequences in healthcare and fintech. This research is crucial for enhancing security in areas reliant on voice authentication, safeguarding confidential data, and preserving the integrity of vital services. The Polish National Center for Research and Development (NCBR) initially supported the project “BIOPUAP” (POIR.01.01.01-0092/19), which focused on digital banking. Subsequently, the project “ADMEDVOICE” (INFOSTRATEG4/0003/2022), also supported by the NCBR, conducted further research into voice cloning in the healthcare sector.