ENF Extraction From Digital Recordings Using Adaptive Techniques and Frequency Tracking

A novel forensic tool used for assessing the authenticity of digital audio recordings is known as the electric network frequency (ENF) criterion. It involves extracting the embedded power line (utility) frequency from said recordings and matching it to a known database to verify the time the recording was made, and its authenticity. In this paper, a nonparametric, adaptive, and high resolution technique, known as the time-recursive iterative adaptive approach, is presented as a tool for the extraction of the ENF from digital audio recordings. A comparison is made between this data dependent (adaptive) filter and the conventional short-time Fourier transform (STFT). Results show that the adaptive algorithm improves the ENF estimation accuracy in the presence of interference from other signals. To further enhance the ENF estimation accuracy, a frequency tracking method based on dynamic programming will be proposed. The algorithm uses the knowledge that the ENF is varying slowly with time to estimate with high accuracy the frequency present in the recording.