VocaLyze – AI Based Emotion Recognition from Voice

Abstract: When a Person emotion change Changes can be seen in their voice tone, pitch speaking speed and intensity. The name of our project is VocaLyze. It is an AI-based web application that identifies a person emotion from their voice. In this system the user can provide their voice in two ways first by recording their voice using a microphone and second by uploading an existing audio file. After receiving the voice, the system first removes background noise and unwanted silent parts from the audio. Then the system extracts voice features such as MFCC, pitch, energy and spectral features. These features are then given to machine Learning and Deep Learning models such as Random Forest, SVM, CNN and LSTM. These models help the system to identify and classify the emotion present in the user voice. The system also provides a confidence score for the detected emotion. Our project does not only identify the emotion. It also provides recommendations according to the detected emotion. These recommendations can include quotes, calming music, breathing, meditation and wellness activities.

Keywords: Artificial Intelligence, Machine Learning, Voice Emotion Recognition, MFCC, CNN, LSTM, Emotion Classification, Personalized Recommendation.