An MFCC‐based text‐independent speaker identification system for access control

Abstract

Summary In recent years, by merit of convenient and unique features, bio‐authentication techniques have been applied to identify and authenticate a person based on his/her spoken words and/or sentences. Among these techniques, speaker recognition/identification is the most convenient one, providing a secure and strong authentication solution viable for a wide range of applications. In this paper, to safeguard real‐world objects, like buildings, we develop a speaker identification system named mel frequency cepstral coefficients (MFCC)‐based speaker identification system for access control (MSIAC for short), which identifies a speaker U by first collecting U 's voice signals and converting the signals to frequency domain. An MFCC‐based human auditory filtering model is utilized to adjust the energy levels of different frequencies as U 's voice quantified features. Next, a Gaussian mixture model is employed to represent the distribution of the logarithmic features as U 's specific acoustic model. When a person, eg, x , would like to access a real‐world object protected by the MSIAC, x 's acoustic model is compared with known‐people's acoustic models. Based on the identification result, the MSIAC will determine whether the access will be accepted or denied.