A Novel Embedded Speaker Verification on System on Chip

This paper realizes a Text-Independent, Speaker Verification system on a System on Chip (SOC) platform. The system uses Mel-Frequency Cepstral Coefficients (MFCC) features with a Gaussian Mixture Model-Universal Background Model ( GMM-UBM ) speaker model. To deal with resource limitations, a new speaker-centric score normalization technique is introduced. This normalization technique results in a relative EER reduction of 44.9% compared to no normalization.