Algorithm for Extracting MFCC Parameters from Audio Signals

This is a self-developed algorithm for extracting MFCC parameters from audio signals, implemented using MATLAB. The algorithm is based on the Mel-frequency cepstral coefficient (MFCC) feature extraction methodology, which effectively transforms audio signals into feature vectors suitable for various audio processing and recognition tasks. The implementation includes key steps such as pre-emphasis filtering, frame blocking, Hamming window application, Fast Fourier Transform (FFT), Mel-filter bank processing, logarithmic compression, and Discrete Cosine Transform (DCT) for cepstral coefficient extraction. The algorithm has demonstrated robust performance and high accuracy in practical applications. Researchers are encouraged to study, modify, and improve this implementation, and share their insights and results. It is hoped that this algorithm implementation will contribute to advancements in audio-related research and applications. The MATLAB code provides clear function modularization, including main feature extraction functions, parameter configuration sections, and visualization routines for analyzing the MFCC feature matrices.