An Automatic Method of Detecting Audio Signal Tampering in Forensic Phonetics
IL-Ho Yang, Kyung-Wha Kim, Myung-Jae Kim, Rock-Seon Baek, Hee-Soo Heo, Ha-Jin Yu · Phonetics and Speech Sciences · 2014
We propose a novel scheme for digital audio authentication of given audio files which are edited by inserting small audio segments from different environmental sources. The purpose of this research is to detect inserted sections from given audio files. We expect that the proposed method will assist human investigators by notifying suspected audio section which considered to be recorded or transmitted on different environments. GMM-UBM and GSV-SVM are applied for modeling the dominant environment of a given audio file. Four kinds of likelihood ratio based scores and SVM score are used to measure the likelihood for a dominant environment model. We also use an ensemble score which is a combination of the aforementioned five kinds of scores. In the experimental results, the proposed method shows the lowest average equal error rate when we use the ensemble score. Even when dominant environments were unknown, the proposed method gives a similar accuracy.