MATLAB Code Implementation for Speech Enhancement Using Wiener Filter

This speech enhancement program is implemented in MATLAB using Wiener filter technique to improve audio quality and clarity, making speech signals more intelligible and easier to understand. The algorithm processes input signals through spectral analysis and noise estimation, where key functions like fft() and ifft() are employed for frequency domain transformations. By applying Wiener filtering principles, the program calculates optimal filter coefficients that minimize mean square error between the original and enhanced signals, effectively reducing background noise while preserving speech components. The implementation includes parameter adjustment capabilities allowing users to modify parameters such as smoothing constants and noise estimation thresholds to adapt to different noise types and acoustic conditions. MATLAB's signal processing toolbox provides efficient matrix operations and visualization tools that enable real-time performance analysis through functions like spectrogram() and audiowrite(). The Wiener filter implementation specifically handles non-stationary noise conditions by continuously updating noise statistics during silent segments detected using voice activity detection (VAD) algorithms. This program demonstrates flexible configuration options where users can experiment with frame sizes, overlap factors, and spectral subtraction parameters to achieve optimal enhancement results for various speech processing applications.