Fig. 1: Overview of the AnuraSet methodological workflow that encompasses the process of dataset creation and benchmarking.
From: A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring
It begins with the collection of passive acoustic monitoring data from four sites in the Neotropics. Subsequently, we annotated the recordings with both weak and strong labels. Leveraging these annotations, we undertook a preprocessing of the data to construct a machine learning-compatible dataset. For solving the problem of anuran call identification, we frame the problem as a multilabel classification challenge, and to establish a baseline model, we adopted a transfer learning approach. Furthermore, we merged a specific task with the dataset, culminating in the creation of a benchmark.
