Computing Fundamental Audio Features with MATLAB

In this implementation, we utilize MATLAB to compute fundamental audio features. These core features include feature statistics, Energy Entropy Standard Deviation (std), mean information entropy, zero-crossing rate detection, and spectral roll-off. By calculating these features, we gain comprehensive insights into audio data characteristics and properties. Feature statistics provide basic statistical information about audio data through functions like mean(), std(), and var(). Energy Entropy Standard Deviation measures the variation in energy distribution across audio frames using energy calculation and entropy analysis algorithms. Mean information entropy reflects the average information content of audio signals, typically implemented with Shannon entropy calculation methods applied to signal probability distributions. Zero-crossing rate detection analyzes waveform characteristics by counting sign changes in the signal using differential and thresholding operations. Spectral roll-off describes frequency decay characteristics through FFT analysis and cumulative energy threshold calculations (typically 85-95% energy cutoff). By employing these features with appropriate MATLAB signal processing toolboxes, we can conduct deeper audio data analysis and extract valuable information for audio classification, segmentation, and content analysis applications.