Utilizing DeepSqueak for automatic detection and classification of mammalian vocalizations: a case study on primate vocalizations.

ABSTRACT: Bioacoustic analyses of animal vocalizations are predominantly accomplished through manual scanning, a highly subjective and time-consuming process. Thus, validated automated analyses are needed that are usable for a variety of animal species and easy to handle by non-programing specialists. This study tested and validated whether DeepSqueak, a user-friendly software, developed for rodent ultrasonic vocalizations, can be generalized to automate the detection/segmentation, clustering and classification of high-frequency/ultrasonic vocalizations of a primate species. Our validation procedure showed that the trained detectors for vocalizations of the gray mouse lemur (Microcebus murinus) can deal with different call types, individual variation and different recording quality. Implementing add

SUBMITTER: Romero-Mujalli D 

PROVIDER: S-EPMC8712519 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature