Goat-Vocalizations

This project aims to classify goat emotions based on vocalizations using machine learning techniques.
We utilized the VOCAPRA dataset, extracting a comprehensive range of temporal and spectral features for analysis.

To explore the feature space, K-means clustering was applied for visualization.
Subsequently, we trained and evaluated three classification models:

• Support Vector Machine (SVM)
• Random Forest
• Neural Network.

Our findings demonstrate that all models effectively classify vocalizations, with the Neural Network achieving the highest accuracy.