Abstract: Audio biometric person authentication is the task of verifying the identity of a person based on the information in the speech signal that occurs during the production of speech. In this research, audio person authentication is focus on acoustic text-dependent speaker verification system. The proposed recognition process begins by converting that audio into frequency domain by applying discrete cosine transform (DCT), then compute the seven moments as a features for that audio and build a database depends on these features, then compute the Kohonen neural network for person identification, and then compute the dynamic time wrapping (DTW) for verification and patterns matching, and later give the decision logic for accepting or rejecting a claimant.