Bird-Call-Classifier

Maschine Learning Pattern Classification Project

The Bird Call Classifier is a robust system for classifying bird calls using Random Forest and neural network models. It extracts meaningful audio features from bird call recordings, engineers a rich set of feature representations, and achieves high accuracy in classifying bird species based on their distinct calls.

Key Features

• Bird Call Classification: Utilizes Random Forest and neural network models to classify bird species based on their distinct calls.
• Model Training: Trains the models on a large and diverse dataset of bird call samples.
• Evaluation and Comparison: Conducts extensive evaluation and comparison of the models' performance, showcasing their effectiveness in accurately identifying different bird species.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/bird-call-classifier.git

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Prepare your bird call recordings and place them in the audio_samples directory.

2. Run the classification script:

   python classify_bird_calls.py

3. View the classification results in the console.

Dataset

The project uses a large and diverse dataset of bird call samples for training and evaluation. Unfortunately, due to licensing restrictions, we cannot provide the dataset directly. However, you can easily obtain bird call datasets from various online sources or record your own samples.

Results

The project achieves high accuracy in classifying bird species based on their distinct calls. The Random Forest and neural network models have been extensively evaluated and compared, demonstrating their effectiveness in accurately identifying different bird species.

License

The Bird Call Classifier project is licensed under the MIT License.

Acknowledgments

We would like to thank the contributors and developers of the libraries and resources used in this project.