Product Description：
. Passive acoustic monitoring (PAM) has the potential to greatly improve our ability to
monitor cryptic yet vocal animals. Advances in automated signal detection have increased the scope of PAM, but distinguishing between individuals—which is necessary
for density estimation—remains a major challenge. When individual identity is known,
supervised classification techniques can be used to distinguish between individuals.
Supervised methods require labelled training data, whereas unsupervised techniques
do not. If the acoustic signals of individuals are sufficiently different, the number of
clusters might represent the number of individuals sampled. The majority of applications of unsupervised techniques in animal vocalizations have focused on quantifying
species-specific call repertoires. However, with increased interest in PAM applications, unsupervised methods that can distinguish between individuals are needed.
