AnuraSet: A dataset for benchmarking Neotropical anuran calls
  identification in passive acoustic monitoring
Juan Sebastián Cañas Maria Paula Toro-Gómez Larissa Sayuri Moreira Sugai Hernán Darío Benítez Restrepo Jorge Rudas Breyner Posso Bautista Luís Felipe Toledo Simone Dena Adão Henrique Rosa Domingos Franco Leandro de Souza Selvino Neckel-Oliveira Anderson da Rosa Vítor Carvalho-Rocha José Vinícius Bernardy José Luiz Massao Moreira Sugai Carolina Emília dos Santos Rogério Pereira Bastos Diego Llusia Juan Sebastián Ulloa
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.