Machine Learning in Authentication of Digital Audio Recordings

Abstract

The field of audio forensics has seen a huge advancement in recent years with an increasing number of techniques used for the analysis of the audio recordings submitted as evidence in legal investigations. Audio forensics involves authentication of the evidentiary audio recordings, which is an important procedure to verify the integrity of audio recordings. This chapter focuses two audio authentication procedures, namely acoustic environment identification and tampering detection. The authors provide a framework for the above-mentioned procedures discussing in detail the methodology and feature sets used in the two tasks. The main objective of this chapter is to introduce the readers to different machine learning algorithms that can be used for environment identification and forgery detection. The authors also provide some promising results that prove the utility of machine learning algorithms in this interesting field.