AHUMADA: A large speech corpus in Spanish for speaker characterization and identification
Speech Communication - Speaker recognition and its commercial and forensic applications
Evaluating digital audio authenticity with spectral distances and ENF phase change
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
"Seeing" ENF: natural time stamp for digital video via optical sensing and signal processing
MM '11 Proceedings of the 19th ACM international conference on Multimedia
How secure are power network signature based time stamps?
Proceedings of the 2012 ACM conference on Computer and communications security
On the music content authentication
Proceedings of the 20th ACM international conference on Multimedia
Exposing digital audio forgeries in time domain by using singularity analysis with wavelets
Proceedings of the first ACM workshop on Information hiding and multimedia security
Optimizing acoustic features for source cell-phone recognition using speech signals
Proceedings of the first ACM workshop on Information hiding and multimedia security
Audio forgery detection based on max offsets for cross correlation between ENF and reference signal
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
Hi-index | 0.00 |
This paper addresses a forensic tool used to assess audio authenticity. The proposed method is based on detecting phase discontinuity of the power grid signal; this signal, referred to as electric network frequency (ENF), is sometimes embedded in audio signals when the recording is carried out with the equipment connected to an electrical outlet or when certain microphones are in an ENF magnetic field. After down-sampling and band-filtering the audio around the nominal value of the ENF, the result can be considered a single tone such that a high-precision Fourier analysis can be used to estimate its phase. The estimated phase provides a visual aid to locating editing points (signalled by abrupt phase changes) and inferring the type of audio editing (insertion or removal of audio segments). From the estimated values, a feature is used to quantify the discontinuity of the ENF phase, allowing an automatic decision concerning the authenticity of the audio evidence. The theoretical background is presented along with practical implementation issues related to the proposed technique, whose performance is evaluated on digitally edited audio signals.