MATLAB-Based Digital Speech Recognition System for 0-9 Digit Identification

This MATLAB-based digital speech recognition system utilizes Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction from audio signals, followed by pattern matching algorithms to identify spoken digits from 0 to 9. The system employs pre-processed training audio samples that capture various vocal patterns and tonal characteristics associated with each digit. Key functions include audio preprocessing (noise reduction, endpoint detection), feature extraction using MATLAB's MFCC implementation, and recognition through dynamic time warping (DTW) or hidden Markov models (HMM). The code structure typically involves training phase (building reference templates) and testing phase (comparing input features with stored patterns). The system's accuracy is enhanced through spectral analysis and temporal pattern matching, making it suitable for applications like voice-activated interfaces and speech-to-text systems. Additional training modules can be implemented to expand recognition capabilities to other vocal patterns using MATLAB's Signal Processing and Audio Toolboxes.