This study investigates the effect of noise on human voice signals and noise reduction efforts using digital signal processing techniques. The objective of this research is to analyze and compare the frequency characteristics and clarity of the original voice signal with those of noise-contaminated signal after undergoing a filtering process in MATLAB. The research methodology includes voice recording, superposition of the voice signal with noise, and filtering using a 50th-order Finite Impulse Response (FIR) low-pass filter with a cutoff frequency of 500 Hz implemented in MATLAB. The analysis is conducted in the frequency domain using the Fast Fourier Transform (FFT) and in the time domain through waveform observation. The results indicate that noise introduces high-frequency components and irregular amplitude fluctuations. After filtering, the high-frequency components are effectively attenuated, resulting in a smoother and more stable signal while preserving the primary characteristics of the human voice. These findings demonstrate that the FIR low-pass filter is effective in improving the quality of human voice signals.
Copyrights © 2026