Source Code for Speech Emotion Recognition

This source code implements speech emotion recognition using MATLAB, designed to analyze common human speech patterns and generate identification markers for emotional states like happiness, sadness, and others. The implementation extracts acoustic features including frequency, pitch, and speech rate from audio signals, then applies machine learning algorithms for emotion classification. The codebase likely includes functions for audio preprocessing (such as MFCC extraction), feature normalization, and classification models (potentially SVM or neural networks). By recognizing emotional states in human speech, this system enables better understanding of user emotions, facilitating more precise services and support. Additionally, this code can be applied to voice assistants, emotion analysis research, and human-computer interaction systems. Key implementation aspects may involve signal processing toolboxes for feature extraction and MATLAB's Classification Learner for model training. We hope this source code proves valuable for your projects!