MATLAB Implementation of Speech Recognition System

Research on MATLAB-based speech recognition systems holds significant importance, particularly in the context of Shenzhen University's speech recognition studies. This system enables identification and comprehension of human language through audio data analysis and processing. The implementation typically involves several key stages: preprocessing with signal filtering techniques, feature extraction using Mel-Frequency Cepstral Coefficients (MFCC), and classification through Hidden Markov Models or Deep Neural Networks. Researchers can utilize this system to enhance speech recognition accuracy and performance by experimenting with different algorithms and optimization techniques. Shenzhen University's contributions to the speech recognition field are particularly valuable, with their work significantly advancing the development of speech recognition technology. Through in-depth research and systematic experiments involving code optimization and parameter tuning, we can continuously improve and refine MATLAB speech recognition systems to meet evolving requirements and challenges in areas like noise robustness and real-time processing.