Voice disguise by mimicry: deriving statistical articulometric evidence to evaluate claimed impersonation

Voice disguise by impersonation is often used in voice-based crimes by perpetrators who try to evade identification while sounding genuine. Voice evidence from these crimes is analyzed to both detect impersonation, and match the impersonated voice to the natural voice of the speaker to prove its correct ownership. There are interesting situations, however, where a speaker might be confronted with voice evidence that perceptually sounds like their natural voice but may deny ownership of it, claiming instead that it is the production of an expert impersonator. This is a bizarre claim, but plausible since the human voice has a great degree of natural variation. It poses a difficult forensic problem: instead of detecting impersonation one must now prove the absence of it, and instead of matching the evidence with the natural voice of the person one must show that they cannot not have a common originator. In this paper we address the problem of disproving the denial of voice ownership from an articulatory-phonetic perspective, and propose a hypothesis testing framework that may be used to solve it. We demonstrate our approach on data comprising voices of prominent political figures in USA, and their expert impersonators.