4.4 Vocal band pass filter

After the inverse filter, we decided to isolate the speech signal to remove some of the additive noise. We accomplished this by applying a band pass filter to the recorded signal. When filtering signals, it is very useful to have an understanding of where the important information in the signal lies. With a speech signal there are a few things that we can take advantage of when attempting to filter out noise.

Speech signals generally have a distinctive envelope in the frequency domain (pictured below). After our preliminary filters, we were able to use this envelope to check and see if our output matched.

Human speech exists within a finite frequency range. As we are trying to eliminate noise to create a more intelligible speech signal we can get rid of everything outside of this range. To do this we will use a band-pass filter. To get optimum intelligibility telephone companies will generally use a window from 300Hz-3600Hz. The military uses around 400Hz-2800Hz to get rid of more background noise. We used a band-pass filter that went from 400Hz-3600Hz. In order to efficiently design this filter to have linear phase and a finite impulse response, we utilized the Remez Exchange (or Parks McClellan) algorithm. We accomplished this in MATLAB, resulting in the frequency response shown below.

Frequency response of bandpass filter