*(Background post for the paper “Improving the frequency response magnitude and phase of*

*analogue-matched digital filters” by John Flynn & Josh Reiss for AES Milan 2018)*

Professional audio mastering is a field that is still dominated by analogue hardware. Many mastering engineers still favour their go-to outboard compressors and equalisers over digital emulations. As a practising mastering engineer myself, I empathise. Quality analogue gear has a proven track record in terms of sonic quality spanning about a century. Even though digital approximations of analogue tools have gotten better, particularly over the past decade, I too have tended to reach for analogue hardware. However, through my research at Queen Mary with Professor Josh Reiss, that is changing.

When modelling an analogue EQ, a lot of focus has been in modelling distortions and other non-linearities, we chose to look at the linear component. Have we reached a ceiling in terms of modelling an analogue prototype filter in the digital domain? Can we do better? We found that yes there was room for improvement and yes we can do better.

The milestone of research in this area is Orfanidis’ 1997 paper “Digital parametric equalizer design with prescribed Nyquist-frequency gain“, the first major improvement over the bilinear transform which has a reknowned ‘cramped’ sound in the high frequencies. Basically, the bilinear transform is what all first generation digital equalisers is based on. It’s high frequencies towards 20kHz drops sharply, giving a ‘closed/cramped’ sound. Orfanidis and later improvements by Massberg [9] & Gunness/Chauhan [10] give a much better approximation of an analogue prototype.

However [9],[10] improve magnitude, they don’t capture analogue phase. Bizarrely, the bilinear transform performs reasonably well on phase. So we knew it was possible.

So the problem is: how do you get a more accurate magnitude match to analogue than [9],[10]? While also getting a good match to phase? Many attempts, including complicated iterative Parks/McClellen filter design approaches, fell flat. It turned out that Occam was right, in this case a simple answer was the better answer.

By combining a matched-z transform, frequency sampling filter design and a little bit of clever coefficient manipulation, we achieved excellent results. A match to the analogue prototype to an arbitrary degree. At low filter lengths you get a filter that performs as well as [9],[10] in magnitude but also matches analogue phase. By using longer filter lengths the match to analogue is extremely precise, in both magnitude and phase (lower error is more accurate)

Since submitting the post I have released the algorithm in a plugin with my mastering company and been getting informal feedback from other mastering engineers about how this sounds in use.

Overall the word back has been overwhelmingly positive, with one engineer claiming it to be the “the best sounding plugin EQ on the market to date”. It’s nice know that those long hours staring at decibel error charts have not been in vain.

Are you heading to AES Milan next month? Come up and say hello!