MATLAB Simulation for Speech Recognition

Conducting MATLAB simulations for speech recognition presents an engaging and challenging project. This implementation utilizes Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction and Dynamic Time Warping (DTW) algorithm for command recognition. The project successfully identifies 10 distinct voice commands through a structured pipeline: pre-emphasis filtering, frame blocking, Hamming window application, FFT transformation, Mel-filter bank processing, and finally DCT compression for MFCC generation. The DTW algorithm handles temporal alignment variations by calculating optimal warping paths between test and reference patterns using dynamic programming. Detailed documentation accompanies the codebase, explaining key MATLAB functions like mfcc() implementation, dtw() path computation, and signal preprocessing techniques. This project enhances practical MATLAB skills while deepening understanding of speech signal processing fundamentals. Participants will learn to apply theoretical concepts through hands-on implementation, developing crucial programming and problem-solving abilities. The simulation serves as an excellent foundation for exploring advanced speech recognition domains while achieving measurable results in command classification accuracy.