Spectrogram-Based Deep Learning Approach for Bird Species Recognition

Birds are essential indicators of ecological health, yet traditional identification methods rely heavily on expert knowledge and visual observation. This paper presents an AI-powered system for automated bird species identification using vocalizations. The solution integrates deep learning models specifically CNNs with a lightweight web application built using modern frontend and backend technologies. It enables users, including researchers and enthusiasts, to identify bird species through sound recordings in real-time. The system also focuses on usability, accessibility, and responsiveness to encourage widespread participation in biodiversity monitoring. Experimental results show that the system performs effectively in species recognition tasks, offering potential for future deployment in field-based conservation efforts.