A workflow for the automated detection and classification of female gibbon calls from long-term acoustic recordings

HIGHLIGHTS

SUMMARY

Increased availability of low-cost recording units (Hill et_al, 2018; Sethi et_al, 2018; Sugai et_al, 2019), along with advances in data storage capabilities, makes the use of PAM an attractive option for monitoring vocal species in inaccessible areas where the animals are difficult to monitor visually (such as dense rainforests) or when the animals exhibit cryptic behavior (Deichmann et_al, 2018). Artificial neural_networks (Mielke and Zuberbühler, 2013), Gaussian mixture models (Heinicke et_al, 2015), and Support Vector Machines (Heinicke et_al, 2015; Keen et_al, 2017) - some of the more commonly used algorithms for early applications of . . .

 



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