Continuants based neural speaker verification system

Abstract

Among the techniques to protect private information by adopting biometrics, speaker verification is widely used due to its advantages in natural usage and inexpensive implementation cost. Speaker verification should achieve a high degree of reliability in verification score, flexibility in speech text usage, and efficiency in the complexity of verification system Continuants have an excellent speaker-discriminant power and the modest number of phonemes in the phonemic category. Multilayer perceptrons (MLPs) have the superior recognition ability and the fast operation speed. In consequence, the two elements can provide viable ways for speaker verification system to obtain the above properties: reliability, flexibility and efficiency. This paper shows the implementation of a system to which continuants and MLPs are applied, and evaluates the system using a Korean speech database. The results of the evaluation prove that continuants and MLPs enable the system to acquire the three properties.