From Clicks to Code: Using Deep Learning and Bioacoustics to Study Orca Whales

Researchers are using deep learning and bioacoustics to study orca whales, as they spend only about 5% of their time near the surface where scientists can observe them. With advancements in technology, hydrophones have become cheaper, smaller, and more durable, allowing researchers to collect massive amounts of ocean recordings. Deep Neural Networks (DNNs) similar to those used in automated speech-to-text models are being employed to parse out orca calls from the reels of hydrophone recordings. ORCA-SPOT is a convolutional neural network model that can automatically find orca vocalizations, boasting a 93.2% accuracy rate. AI models like ORCA-SPOT help researchers better understand orcas' communication and behavior, prevent ship-orca collisions, and enlist citizen scientists in labeling ocean noise data for further research.