This AI project is about identifying bird species by listening to their voices. Sound recording of birds is converted into data and deep learning model is trained to classify birds accurately.
Objective of this project is to develop deep learning model to predict the bird species from audio recordings.
✔ Successfully built a deep learning model that identifies bird species from audio
✔ Achieved strong accuracy even with background noise
✔ Demonstrated real-world application of AI
Dataset Used
Cornell BirdCLEF Dataset
Thousands of bird audio samples
Multiple bird species
Real-world noisy environmental sounds
This dataset is widely used in international AI competitions and research.
Tools & Technologies Used
This project uses industry-relevant AI tools, all of which are covered in our AI course in Pune:
Python – Core programming language
Librosa – Audio processing and feature extraction
Spectrograms & Mel-Spectrograms – Converting sound into visual data
PyTorch – Deep learning framework
Convolutional Neural Networks (CNNs) – For pattern recognition in spectrograms
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