Audio Forgery Detection Techniques: Present and Past Review

The increase in low cost digital audio recorders, mobile applications and accelerating growth of the audio-based Internet of Things (IoT) has initiated ease in obtaining speech and audio data which will be later used for the purpose of identifying human traits, implementing voice authentication system and development of voice based embedded systems. On the other hand, the availability of free advanced mobile applications and audio editing software like Adobe, Audition CC, etc. enabling people to edit easily the meaningful content of audio recordings data for getting benefit from e-services or producing it in a courtroom for the purpose digital proof. Perhaps, most of the people do it for fun as well as the strong intention of hiding reality present. Moreover, the audio recording captured in a real-life today does not contain digital watermarking and signature content for authentication because of expensive procedure. Therefore, in recent years the researches focused more on developing active audio forgery detection techniques for copy-move and audio splicing forgeries to authenticate and verify for its genuineness. In this paper, put an effort to describe past and present developments in audio copy-move and audio splicing forgery techniques. The paper also presents an overview of audio forgeries, its classification, various post-processing operations used and available audio dataset for forgery sample preparation for benchmark testing.