Recording Source Identification Using Device Universal Background Model

The task of recording source identification is to extract digital evidence of device mechanism involved in the generation of the speech signals by analyzing the acoustic signals. This paper proposes a Device Universal Background Model (DEV-UBM) based algorithm for identifying recording devices. When extracting the features of recording devices, the mute voice is extracted from the input speech, and then MFCCs extracted from the mute voice after pre-processing are as the features of recording devices. DEV-UBM is used to represent the model of recording device, and log-likelihood is used to describe the final scores, which are used to classify different recording devices. The experimental result indicates that the mean accuracy of recording device identification on 9 recording devices is 93.16%, which shows the proposed algorithm is effective.