In the fascinating world of bioacoustics, the ability to accurately classify animal sounds plays a significant role in our understanding of biodiversity. The Mixture of Mixups (Mix2) framework introduces a novel approach to classify anuran species sounds by mixing regularization methods—Mixup, Manifold Mixup, and MultiMix—effectively overcoming the challenges of multi-label imbalanced classification.

• The Mix2 framework accurately identifies rare sounds with limited occurrences.
• It adapplies mixing regularization methods randomly during training iterations.
• The method improves the robustness of classifications in bioacoustic analysis.
• It provides deep insights into the ecosystem by monitoring anuran species sounds.

The implications of this research are profound, offering a new pathway for conservationists and researchers to monitor and protect species through sound. The innovative use of Mix2 could also pioneer similar strategies in other areas of machine learning, where data imbalance poses a challenge.