Speech Analysis Using MATLAB

This MATLAB toolkit developed by the Electrical Engineering Department at the University of Texas provides comprehensive speech analysis capabilities through multiple specialized functions. The time-domain analysis module enables detailed signal examination using waveform visualization and amplitude-based measurements. Spectrogram analysis utilizes Short-Time Fourier Transform (STFT) implementations to display time-frequency characteristics, allowing researchers to observe spectral patterns and energy distribution. The fundamental frequency extraction employs pitch detection algorithms (such as autocorrelation or cepstral analysis) to identify vocal fold vibration rates. Formant measurement functions implement Linear Predictive Coding (LPC) or spectral peak detection methods to track resonant frequencies of the vocal tract. These integrated functionalities provide substantial assistance in speech analysis by delivering rich informational data and analytical insights, enabling users to better understand and investigate speech signals through practical code implementations.