Published Paper Details:

This project aims to advance avian identification through the utilization of audio signals, employing a comprehensive approach that integrates with deep learning techniques. The study focuses on developing three distinct models: Ridge Classifier, Support Vector Machine (SVM) Classifier, and Artificial Neural Network (ANN). By converting audio signals into numerical data using standard Python libraries, we aim to create robust models capable of accurately identifying bird species based on their distinct audio signatures. The Ridge and SVM classifiers, representing classical ML paradigms, will leverage advanced feature extraction methodologies. Simultaneously, the ANN model, a deep learning approach, will harness the power of neural networks to capture intricate patterns within the audio data. This interdisciplinary fusion of ML and deep learning techniques is poised to significantly enhance avian species identification, contributing to biodiversity monitoring and conservation efforts.