This document is a project report on emotion speech detection. It summarizes the goals of speech emotion recognition, introduces the Python libraries used including librosa and JupyterLab. It describes the hardware and software requirements, and the RAVDESS dataset used. Screenshots are included showing the data exploration and model training process. The report concludes that an MLPClassifier model achieved 82.50% accuracy on this task of recognizing emotions from speech.