  Voice disguise, purposeful modification of one's speaker identity with the
aim of avoiding being identified as oneself, is a low-effort way to fool
speaker recognition, whether performed by a human or an automatic speaker
verification (ASV) system. We present an evaluation of the effectiveness of age
stereotypes as a voice disguise strategy, as a follow up to our recent work
where 60 native Finnish speakers attempted to sound like an elderly and like a
child. In that study, we presented evidence that both ASV and human observers
could easily miss the target speaker but we did not address how believable the
presented vocal age stereotypes were; this study serves to fill that gap. The
interesting cases would be speakers who succeed in being missed by the ASV
system, and which a typical listener cannot detect as being a disguise. We
carry out a perceptual test to study the quality of the disguised speech
samples. The listening test was carried out both locally and with the help of
Amazon's Mechanical Turk (MT) crowd-workers. A total of 91 listeners
participated in the test and were instructed to estimate both the speaker's
chronological and intended age. The results indicate that age estimations for
the intended old and child voices for female speakers were towards the target
age groups, while for male speakers, the age estimations corresponded to the
direction of the target voice only for elderly voices. In the case of intended
child's voice, listeners estimated the age of male speakers to be older than
their chronological age for most of the speakers and not the intended target
age.
