Dr Emmanuel Dufourq, AIMS-Carnegie Junior Research Chair and PI: Machine Learning for Ecology Research Group in the AIMS South Africa Research Centre was part of a recent publication that represents a significant step forward in applying artificial intelligence (AI) to bioacoustics. A diverse team of researchers from around the globe joined forces to address current challenges and explore future possibilities for integrating AI within bioacoustic research. This work highlights the importance of bridging expertise across fields to foster innovation.

One of the primary goals of this project was to address the existing gap in expertise between the biological sciences and the fields of machine learning and computer science. The paper begins by offering an accessible overview of the requirements for automatic detection in bioacoustics, designed to introduce computer scientists to the needs of bioacoustics professionals. In turn, it also equips biologists with essential machine learning and AI concepts, empowering them to incorporate automated detection systems into their research. In addition to providing a thorough step-by-step guide on creating an automatic detection pipeline, the paper offers insights into future directions for AI in bioacoustics, aiming to streamline workflows and improve ecological monitoring globally.