Bird Sound

Bird sound analysis focuses on automatically identifying bird species and individuals from their vocalizations, primarily to monitor biodiversity and understand avian behavior. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformer networks, and fully convolutional networks (FCNs) for classification, often incorporating techniques like transfer learning and self-supervised learning to address data limitations. These advancements enable more efficient and accurate species identification, even in challenging scenarios with limited labeled data or noisy soundscapes, supporting ecological monitoring and conservation efforts.