Developing an AI-Powered Bird Sound Recognition System for Monitoring Avian Biodiversity in Belarus

Abstract

This paper explores the application of artificial intelligence (AI) of automated bird vocalisation recognition for the purpose of continuous monitoring of avian species in Belarus. It presents a novel system comprising a large, annotated dataset of Belarusian bird sounds, a convolutional neural network model trained for multi-label species identification, and a publicly available software platform. The AI-driven approach of the system enables efficient analysis of large audio datasets and real-time species identification. This research demonstrates the feasibility of using AI to overcome challenges in biodiversity monitoring and lays the groundwork for future advancements in automated wildlife conservation.