MATLAB Training Program for Digital Speech Recognition

This documentation discusses MATLAB implementation for digital speech recognition systems. Given the substantial volume of training and recognition data required for comprehensive model development, we provide only a limited dataset sample. However, users can generate additional custom samples using audio editing tools like COOLEDIT. The audio specifications require WAV files with 8000 Hz sampling rate, mono channel configuration, 16-bit resolution in Motorola PCM format. Corresponding LAB files must contain timestamp markers for speech segment boundaries (start/end points) along with phonetic transcriptions. For MATLAB implementation, key functions like audioread() would handle waveform loading, while signal processing techniques (MFCC feature extraction using melSpectrogram()) and machine learning classifiers (HMM or neural networks via classify()) would form the core recognition algorithm. This approach enables developers to create expanded datasets for more robust digital speech recognition testing and model training.