Same data, different results? Machine learning approaches in bioacoustics
K. Wierucka, D. Murphy, S. K. Watson, N. Falk, C. Fichtel, J. Leon, S. T. Leu, P. M. Kappeler, E. F. Briefer, M. B. Manser, N. Phaniraj, M. Scheumann, J. M. Burkart
The paper evaluates machine learning methods for caller identity classification in mammalian vocalizations, finding Mel-frequency cepstral coefficients and random forests provide consistent results across datasets.
bioRxiv · Apr 14, 2024Animal Behavior & Cognition