On Robust Electric Network Frequency Detection Using Huber Regression.

A robust regression technique known as Huber regression is incorporated into the Electric Network Frequency (ENF) detection task. This novel framework is based on the assumption of a mixture noise model, which combines Gaussian and Laplacian noise for ENF detection in short-length audio recordings. The effectiveness of the proposed ENF detector is assessed through accuracy calculations and the analysis of the Receiver Operating Characteristic curve with respect to the Area Under the Curve. Real-world benchmark data from the ENF-WHU dataset are utilized for this evaluation. The experimental results indicate that integrating the Huber regression method leads to a significant enhancement in ENF detection for short-length audio recordings, outperforming the performance of existing state-of-the-art techniques.