Application of a semi-automated vocal fingerprinting approach to monitor Bornean gibbon females in an experimentally fragmented landscape in Sabah, Malaysia

Vocal individuality has been documented in a variety of mammalian species and it has been proposed that this individuality can be used as a vocal fingerprint to monitor individuals. Here we provide and test a classification method using Mel-frequency cepstral coefficients (MFCCs) to extract features from Bornean gibbon female calls. Our method is semi-automated as it requires manual pre-processing to identify and extract calls from the original recordings. We compared two methods of MFCC feature extraction: (1) averaging across all time windows and (2) creating a standardized number of time wi... Mehr ...