A few questions...

Special Interest Groups Recording Equipment
1

  1. I have been trying to download plug-ins for Audacity 1.2.6 and they are not being recognized in the program. I have Windows Vista, which may be the problem. If that is the problem can someone direct me to a site that has Vista compatible plug-ins? If Vista is not the problem I would like to know what I am doing wrong. So far I am just unzipping the files and dragging the .dll files into the plug-in file of Audacity but they do not appear even when i restart my computer.

  2. Can someone explain FTT Filtering indepth to me?

  3. What order should I apply clean up effects like Click Removal, Compression, and Noise Removal?


    Thank you

2

  1. Without you tell us what plug-ins, and where you have tried to put them, we can’t help. Try the audacity 1.2.x forum for you operating system with that bit of the question.

  2. Do you have two years for a university course? The the theory is a bit complicated, the maths is very complicated.

  3. Noise removal first, because it needs to be applied as close to the source of the noise as possible. Compression comes after click removal, so the clicks don’t confuse it. That leaves us with Noise Removal, Click Removal, Compression.

3

Regarding FFT. Yes, the math is complicated. I had a digital signal processing course in college and I still could not easily write an FFT routine.

A Fourier Transform takes a data set in the time domain and translates it to the frequency domain or back again. When you record audio, it is a series of samples of the intensity of sound with respect to time. Doing a Fourier Transform on it then shows the spectrum, i.e. what frequencies are in the sample and how much of each is present.

Once you have a frequency domain data set, you can manipulate it, then convert back to time. This is one way to do equalization or pitch shifting. Often it is just used to analyze the audio. For example, you can play a burst of white noise in your recording space and then sample that. When you look at the spectrum of your recorded noise, you can identify frequency response problems in your space or find frequencies that are likely to cause feedback in a live performance.

An FFT is just a fast implementation of the Fourier Transform that imposes some constraints on the sample size (usually powers of 2) and often uses table-lookups for some intermediate calculations.