Animal Sound Classification Using Machine Learning (Dog, Cow, Frog)

In this project, I developed a machine learning model to classify animal sounds into three categories: dog, cow, and frog. The model was trained on audio clips and used signal processing techniques to extract relevant audio features such as MFCCs (Mel-Frequency Cepstral Coefficients).

I used Python along with libraries such as librosa for audio analysis and scikit-learn for training and evaluation. This project demonstrates my ability to work with audio data, perform feature extraction, and build classification models.

The final model achieved high accuracy in classifying unseen audio clips and can be used as a basic sound recognition system.