• Version
• Download 11
• File Size 392.55 KB
• File Count 1
• Create Date 11 June 2025
• Last Updated 11 June 2025

Bird Sound Prediction

Authors:

Rajlaxmi Kasture, Sujata Patil

  Rajlaxmi S. Kasture MCA & Trinity Academy of Engineering, Pune

 Sujata R. Patil MCA & Trinity Academy of Engineering, Pune

ABSTRACT - This paper presents a machine learning-based system designed for recognizing bird species from their vocalizations. Leveraging Artificial Neural Networks (ANNs), specifically a Multilayer Perceptron (MLP), the system processes pre-recorded bird calls, extracts Mel Frequency Cepstral Coefficients (MFCCs), and classifies the sound using a trained ANN model. The proposed system is computationally efficient and accurate, making it a valuable tool for ecological research and conservation. The system is deployed via a user-friendly Flask web interface for real-time usage.

Keywords: Bird Sound Recognition, Deep Learning, MFCC, Librosa , TensorFlow, Flask

KeyWords:  optics, photonics, light, lasers, stencils, journals