MATLAB Program Code for Adding Noise to Audio Signals

The following MATLAB program code provides a practical implementation for adding controlled noise to audio signals. This technique is essential for simulating real-world scenarios and testing the robustness of various signal processing algorithms. The core algorithm utilizes white Gaussian noise generation with precise Signal-to-Noise Ratio (SNR) control. The implementation follows these key steps: 1. Audio file loading using audioread() function 2. Noise generation through randn() function creating normally distributed random values 3. SNR-based noise power normalization using vector norms 4. Signal superposition combining original audio with generated noise MATLAB Code Implementation: % Load audio data from WAV file [y, Fs] = audioread('your_audio_file.wav'); % Configure SNR and generate Gaussian noise SNR = 10; % Define Signal-to-Noise Ratio in dB noise = randn(size(y)); % Create noise vector matching audio dimensions noise = noise / norm(noise) * norm(y) / 10^(SNR/20); % Normalize noise power based on SNR % Create noisy signal by additive combination y_noisy = y + noise; % Play resulting audio through system speakers sound(y_noisy, Fs); % Save processed audio to new file audiowrite('your_audio_file_noisy.wav', y_noisy, Fs); This implementation serves as a fundamental tool for audio processing applications including speech recognition systems, noise reduction algorithms, and audio compression techniques. The code structure allows easy modification for different noise types (pink noise, brown noise) by replacing the randn() function with appropriate noise generation methods. Researchers and audio engineers can utilize this code to evaluate algorithm performance under various noise conditions and develop more robust signal processing solutions.