Speech Emotion Recognition for Specific Demographic Groups

The MATLAB code package implements a novel research framework for "Speech Emotion Recognition for Specific Demographic Groups." Detailed technical specifications are provided in the accompanying research paper. This research aims to analyze emotional expressions within specific populations using speech processing techniques. The implementation involves signal processing algorithms that extract acoustic features from voice signals to identify characteristic patterns under different emotional states. Key functions include Mel-frequency cepstral coefficients (MFCC) extraction, prosodic feature analysis, and machine learning classification algorithms (such as SVM or neural networks) for emotion categorization. By processing and analyzing speech signals, the system can recognize vocal characteristics corresponding to various emotional states, facilitating deeper research into human emotional expression mechanisms. This study holds significant importance for advancements in emotion recognition technology and human-computer interaction systems. Through this implementation and the accompanying paper, we aim to provide references and inspiration for researchers in related fields, promoting further development in this domain.