Audio source authentication and splicing detection using acoustic environmental signature

Zhao, Hong1; Chen, Yifan1; Wang, Rui1; Malik, Hafiz2

10.1145/2600918.2600933

2014

2nd ACM Workshop on Information Hiding and Multimedia Security, IH and MMSec 2014

159-164

Salzburg, Austria

Association for Computing Machinery, Inc

Audio splicing is one of the most common manipulation techniques in the audio forensic world. In this paper, the magnitudes of acoustic channel impulse response and ambient noise are considered as the environmental signature and used to authenticate the integrity of query audio and identify the spliced audio segments. The proposed scheme firstly extracts the magnitudes of channel impulse response and ambient noise by applying the spectrum classification technique to each suspected frame. Then, correlation between the magnitudes of query frame and reference frame is calculated. An optimal threshold determined according to the statistical distribution of similarities is used to identify the spliced frames. Furthermore, a refining step using the relationship between adjacent frames is adopted to reduce the false positive rate and false negative rate. Effectiveness of the proposed method is tested on two data sets consisting of speech recordings of human speakers. Performance of the proposed method is evaluated for various experimental settings. Experimental results show that the proposed method not only detects the presence of spliced frames, but also localizes the forgery segments. Comparison results with previous work illustrate the superiority of the proposed scheme.
Copyright 2014 ACM.

第一

EI

20154001326016

Audio acoustics ; Impulse response

Acoustic Waves:751.1 ; Acoustic Noise:751.4

EV Compendex

1.Department of Electrical and Electronic Engineering, South University of Science and Technology of China, Shenzhen, China
2.Department of Electrical and Computer Engineering, University of Michigan, Dearborn; MI; 48128, United States

Zhao, Hong,Chen, Yifan,Wang, Rui,et al. Audio source authentication and splicing detection using acoustic environmental signature[C]:Association for Computing Machinery, Inc,2014:159-164.