Odyssey 2016

Technologies of biometric template protection grant a significant improvement in data privacy and increase the likelihood that the general public will effectively consent in the biometric system usage. Focusing on speaker recognition this area of research is still in its infancy. Previously proposed voice biometric template protection schemes fail in guaranteeing required properties of irreversibility and unlinkability without significantly degrading the recognition accuracy. A crucial step for accurate and secure template protection schemes is the feature type transformation which might be required to binarize extracted feature vectors. In this paper we introduce a binarization technique for voice biometric features called multi-bit allocation. The proposed scheme, which builds upon a GMM-UBM-based speaker recogniton system, is designed to extract discriminative compact binary feature vectors to be applied in a voice biometric template protection scheme. In a preliminary experimental study we show that the resulting binary representation causes only a marginal decrease in biometric performance compared to the baseline system, confirming the soundness and aplicability of the proposed scheme.