Is there an 'A' Weighting option in the spectrum analysis


I measure sound using a sound level meter.

I have the option of recording the sound which I always do.

My sound level meter software allows 1/3 octave analysis but will not drill down any further so I use Audacity to look for specific frequencies to allow me to specify accurate noise control solutions.

I have a particular problem at the moment where a very low level of sound is heard, below LAeq 30dB.

When I use Audacity and the analyze, plot spectrum, the scale on the left starts at -47dB and ends at -90dB with frequencies from 0 to 8000Hz. (my meter measures up to 20kHz).

The problem I have is that the human ear cannot hear very low frequencies and this is the majority of the graph. Is there an option to ‘A’ weight the data to pick out frequencies that can be heard?

Thank you


There is no built-in A weighting filter, but you could create one in the Equalization effect:
See this page about managing Eq curves:
and this page about custom curves (includes a link to an A-weighting filter curve):

The frequency range of Plot Spectrum depends on the sample rate. Digital audio can represent frequencies up to half the sample rate, so for example, if the sample rate is 16000 Hz, then the available frequency bandwidth is 0 to 8000 Hz.

to specify accurate noise control solutions.

There are conditions where flat analysis is handy and they’re not obvious. Many USB microphones generate their own very low frequency noise and trash independent of that’s going on In Real Life. I’m guessing the makers say: nobody can hear it, so why bother to filter low pitched noise out? It adds to the cost.

No, you can’t hear them, but the audio processing tools and filters can and it throws off sound processing. This drives the audiobook people nuts.


Thanks for the replies guys, I will try to create an ‘A’ weighting filter in the Equalization effect :open_mouth: :slight_smile:

Hello All,

I added the ‘A’ weighting curve and it works a treat. All instructions were supplied by Steve through the links.

Spot on.

Thank you,