Spectrogram Analysis of Speech Data in MATLAB: Narrowband and Wideband Visualization

This implementation demonstrates spectrogram analysis of speech data using MATLAB, generating both narrowband and wideband visualizations. Spectrogram analysis provides crucial insights into the spectral characteristics and temporal variations of speech signals. The narrowband spectrogram implementation typically uses a longer window length (e.g., 30-50 ms) with high frequency resolution, allowing detailed observation of harmonic structures and formant patterns through MATLAB's spectrogram function with appropriate windowing parameters. The wideband spectrogram employs shorter window durations (5-20 ms) with superior temporal resolution, effectively capturing rapid speech transitions and plosive sounds using algorithms like the short-time Fourier transform (STFT). Such analysis enables in-depth investigation of speech signal properties and delivers valuable information for speech processing, recognition systems, and acoustic research applications. Key MATLAB functions involved include spectrogram(), stft(), and various window functions (hamming, hanning) with configurable overlap percentages for optimal time-frequency representation.