Feasibility of Using Electrical Network Frequency Fluctuations to Perform Forensic Digital Audio Authentication

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Université d'Ottawa / University of Ottawa

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Extracting the Electric Network Frequency (ENF) fluctuations from an audio recording and comparing it to a reference database is a new technology intended to perform forensic digital audio authentication. The objective of this thesis is to implement and design a range of programs and algorithms for capturing and extracting ENF signals. The developed C-program combined with a probe can be used to build the reference database. Our implementation of the Short-Time Fourier Transform method is intended for the ENF extraction of longer signals while our novel proposed use of the Autoregressive parametric method and our implementation of the zero-crossing approach tackle the case of shorter recordings. A Graphical User Interface (GUI) was developed to facilitate the process of extracting the ENF fluctuations. The whole process is tested and evaluated for various scenarios ranging from long to short recordings.

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Forensic, Digital, ENF, Electrical Network Frequency, Autoregressive, AR model, parametric, zero-crossing, Fourier Transform, FFT, STFT, Short time fourier transform, fluctuation, correlation, authentic, audio, Digital Signal Processing

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