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Cornell researcher builds groundbreaking machine learning toolkit for bioacoustics

Cornell researcher builds groundbreaking machine learning toolkit for bioacoustics

Significant advances have recently been made in bioacoustic deep learning techniques — a method for automated detection of animal sounds — at Cornell’s K.Lisa Yang Center for Bioacoustics Conservation. Dr. Shyam Madhusudhana, a postdoctoral researcher in the Lab of Ornithology, has built a toolkit that enables bioacoustics to create complex voice recognition models with just a few lines of code.

The Koogu toolkit was used in a recent study that outperformed marine analysts in spotting blue D whale calls.

Blue whale D-calls are calls of varying frequency produced by male and female whales, unlike the well-known whale song produced only by males. While whale songs are often predictable and easily identifiable, D calls are erratic and are produced less frequently.



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