Revisiting Carl Bildt’s Impostor: Would a Speaker Verification System Foil Him?

Abstract

Impostors pose a potential threat to security systems that rely on human identification and verification based on voice alone and to security systems that make use of computer audio-based person authentication systems. This paper presents a case-study, which explores these issues using recordings of a high quality professional impersonation of a well-known Swedish politician. These recordings were used in the role of impostor in the experiments reported here. The experiments using human listeners showed that an impostor who can closely imitate the speech of the target voice can result in confusion and, therefore, can pose a threat to security systems that rely on human identification and verification. In contrast, an established Gaussian mixture model based speaker identification system was employed to distinguish the recordings. It was shown that the recognition engine was capable of classifying the mimic attacks more appropriately.