Identifying and building on the current state of bioacoustics software

Abstract

Bioacoustics is a powerful and increasingly commonly used tool for terrestrial and marine biological assessments. As the scale of bioacoustic data collection has increased, techniques for processing these data have diversified. However, with analysis methods rapidly evolving and dozens of analysis software packages already available, it is challenging to identify which software, if any, meets a particular researcher’s needs. We reviewed bioacoustics software to identify packages aimed at or used by bioacoustics researchers in ecology. We compiled descriptions of the function of 65 stable or actively developed software packages used for bioacoustics analyses. Of these, 59 were free or open-source packages. In addition, we developed free, open-source Python software, OpenSoundscape, that addresses gaps in available software. OpenSoundscape simplifies the process of creating flexible, scalable deep learning algorithms for bioacoustic analysis. It can be used to train binary or multiclass convolutional neural networks with any PyTorch-implemented model structure (e.g., ResNet50, Inception v3). Researchers can easily customize its spectrogram preprocessing and data augmentation routines to improve model performance. OpenSoundscape also includes modules to work with annotated acoustic data, apply additional signal processing algorithms, perform acoustic localization, and “open the black box” of deep learning using Grad-CAM.