MATLAB Code for Spectrogram Plotting with SNR and MSE Analysis

The provided code contains three crucial components for audio signal analysis: spectrogram generation, signal-to-noise ratio (SNR) computation, and mean square error (MSE) calculation. These elements are fundamental in audio processing workflows for assessing signal quality and characteristics. The spectrogram implementation typically utilizes MATLAB's spectrogram function or short-time Fourier transform (STFT) to visualize frequency components over time, providing insights into the spectral content evolution. The SNR calculation code compares the power of the original signal against background noise using logarithmic decibel scaling, essential for quantifying audio clarity. The MSE component implements squared error averaging between reference and processed signals, serving as a key metric for evaluating processing accuracy. These code segments employ matrix operations and statistical functions native to MATLAB, requiring proper parameter tuning for window size, overlap, and frequency resolution. Understanding these implementations is critical for effective audio data processing and algorithm validation.