Design and Characteristic Analysis of Blackman Window-Based Fir Low-Pass Filter for Digital Speech Signal Processing

Abstract

Digital signal processing plays an important role in audio signal analysis, particularly in separating signal components based on their frequency characteristics. One commonly used technique is digital filtering, which can be applied to reduce unwanted frequency components in speech signals. This study aims to design and analyze the characteristics of a Finite Impulse Response Low-Pass Filter using the Blackman Window method for digital speech signal processing. The filter was designed with a sampling frequency of 48 kHz, a cutoff frequency of 6 kHz, a transition band of 2 kHz, and a filter order of 131. The analysis was conducted by observing the filter response and the signal characteristics in both the time and frequency domains before and after filtering. The results show that the designed filter has low-pass characteristics, allowing low-frequency components to pass while attenuating high-frequency components above the cutoff frequency. The magnitude response indicates a significant attenuation in the stopband region, while the phase response shows a relatively linear pattern, which is an important characteristic of FIR filters in preserving signal waveform integrity. In addition, the symmetrical impulse response confirms the linear phase behavior of the designed filter. Based on these results, the Blackman Window-Based FIR Low-Pass Filter can be used as a basic digital filtering approach for speech signal processing applications.