Neuro-fuzzy-based biometric system using speech features
Anupam Shukla, Ritu Tiwari, Chandra Prakash Rathore · International Journal of Biometrics · 2010
Biometric identification is one of the most developing areas. In this paper, a biometric system is simulated using speech features, which identifies the speaker along with their gender and mental status. Work here is broadly classified into two parts, i.e., extraction of the speech features, namely Pitch, Amplitude, Number of Zero-Crossing (NZC), Average Power Spectral Density (PSD) content in the speech of informant and in the second part an adaptive neuro-fuzzy based simulation model has been developed for speaker identification along with their gender and mental status. The recognition score varies depending on different input and output Membership Functions (MFs).