This repo contains the ENF-WHU audio recording dataset collected around Wuhan University campus and the MATLAB programs for electronic network frequency (ENF) detection, enhancement, and robust estimation, in ENF-based audio forensic applications.
The ground-truth matched location (the lag that corresponding to the true timestamp) within the one day reference can be obtained by matching the noise-free ref files with the corresponding one day ref. For example, we can match "003_ref.wav" in "H1_ref" folder within "003-004_ref.wav" in "H1_ref_one_day" folder, and the matched lag index is the "ground truth" timestamp for recording "003.wav" in "H1" folder, meaning that "003.wav" should be matched at the same or a very close lag index in "003-004_ref.wav". Both MSE and CC can be used for the matching criterion as long as the recording and ref are matched using the same criterion.
It contains our proposed ENF enhancement and estimation methods including
in comparison with the following existing works
evaluated using both synthetic data and the real-world recordings from the ENF-WHU dataset.
[1] G. Hua, H. Liao, Q. Wang, H. Zhang, and D. Ye, "Detection of electric network frequency in audio recordings – From theory to practical detectors," IEEE Trans. Inf. Forensics Security, vol. 16, pp. 236–248, 2021. link
[2] G. Hua, H. Liao, H. Zhang, D. Ye, and J. Ma, "Robust ENF estimation based on harmonic enhancement and maximum weight clique," IEEE Trans. Inf. Forensics Security, DOI: 10.1109/TIFS.2021.3099697, 2021. link
[3] G. Hua and H. Zhang, "ENF signal enhancement in audio recordings," IEEE Trans. Inf. Forensics Security, vol. 15, pp. 1868-1878, 2020. link
[4] G. Hua, "Error analysis of forensic ENF matching," in Proc. 2018 IEEE International Workshop on Information Forensics and Security (WIFS), pp. 1-7, Hong Kong, Dec. 2018. link
[5] G. Hua, G. Bi, and V. L. L. Thing, "On practical issues of electric network frequency based audio forensics," IEEE Access, vol. 5, pp. 20640-20651, Oct. 2017. link
[6] G. Hua, Y. Zhang, J. Goh, and V. L. L. Thing, "Audio authentication by exploring the absolute error map of the ENF signals," IEEE Trans. Inf. Forensics Security, vol. 11, no. 5, pp. 1003-1016, May 2016. link
[7] G. Hua, J. Goh, and V. L. L. Thing, “A dynamic matching algorithm for audio timestamp identification using the ENF criterion,” IEEE Trans. Inf. Forensics Security, vol. 9, no. 7, pp. 1045-1055, Jul. 2014. link