Voice Signal Filtering Processing

In voice signal processing, sampling is first performed to obtain discrete digital signals. Subsequently, spectral analysis can be conducted to study the frequency components and energy distribution of the signal. For enhanced processing and analysis, we can design low-pass and high-pass filters. Low-pass filters can eliminate noise by removing high-frequency components, while high-pass filters can emphasize high-frequency portions of the signal by eliminating low-frequency components. During filter design, we may choose between IIR (Infinite Impulse Response) or FIR (Finite Impulse Response) filters to better accommodate different processing requirements. IIR filters typically provide sharper cutoffs with fewer coefficients but may introduce phase distortion, whereas FIR filters offer linear phase characteristics at the cost of higher computational complexity. Through these processing and analysis steps, we can better understand and utilize the information contained in voice signals. Common implementation approaches include using functions like butter() for IIR filter design and fir1() for FIR filter design in signal processing toolboxes, followed by application through filtering operations such as filtfilt() for zero-phase filtering.