2023/07/11 by Juan Sebastián Cañas, Cañas, Juan Sebastián, María Paula Toro-Gómez +35 · 5 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Environmental Science · #Amphibian and Reptile Biology #Animal Vocal Communication and Behavior #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Music and Audio Processing #Sound (cs.SD) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2307.06860
openalex publication_date 2023/07/11 · openalex created_date 2023/07/15 · openalex updated_date 2026/08/01
Global change is predicted to induce shifts in anuran acoustic behavior, which can be studied through passive acoustic monitoring (PAM). Understanding changes in calling behavior requires the identification of anuran species, which is challenging due to the particular characteristics of neotropical soundscapes. In this paper, we introduce a large-scale multi-species dataset of anuran amphibians calls recorded by PAM, that comprises 27 hours of expert annotations for 42 different species from two Brazilian biomes. We provide open access to the dataset, including the raw recordings, experimental setup code, and a benchmark with a baseline model of the fine-grained categorization problem. Additionally, we highlight the challenges of the dataset to encourage machine learning researchers to solve the problem of anuran call identification towards conservation policy. All our experiments and resources can be found on our GitHub repository https://github.com/soundclim/anuraset.