GOLDBERG AND MÄKIVIRTA
OPTIMISED EQUALISATION COMPARISON
AES 116TH CONVENTION, BERLIN, GERMANY, 2004 MAY 8-11
7
also the probable cause for improving performance
towards larger systems (Figures 4 and 14) shown by a
similar trend across both equalisation methods. This
underlines the importance of primarily solving acous-
tical problems by treating the room before trying to
use equalisers.
Graphic equalisation can yield a somewhat flatter re-
sponse, but multiple filter bands may be required to
correct for large features in the response. Some up-
ward deviations in the response, due to resonances or
constructive interference, cannot be corrected accu-
rately when they do not coincide with the graphical
equaliser’s centre frequencies. This complexity of
graphical equalisers makes manual gain setting com-
plex and therefore more prone to operator error. When
using computerised optimisation, the time to calculate
a graphical equaliser’s settings was 8-48 times longer
than the time to select the best room response control
settings.
Graphic equalisation achieves LF subband results
closer to the target. Both equalisation techniques
achieved a similar improvement in the broadband bal-
ance, which has previously been shown to determine a
subjective lack of colouration in sound systems.
7. CONCLUSIONS
The objective of this paper is to compare the perform-
ance of the industry standard 31-band graphic equal-
iser to the room response controls built into active
loudspeakers. Both equalisation techniques achieved a
similar improvement in the broadband balance, which
has previously been shown to determine a subjective
lack of colouration in sound systems. For all loud-
speaker models pooled together, the room response
controls improved the RMS deviation from 6.1 dB to
4.7 dB (improvement 22%), whereas graphic equalisa-
tion improved the RMS deviation to 1.8 dB (im-
provement 70%). The graphical equaliser achieves
this improvement by using between eight (large loud-
speakers) and ten times (small two-ways) more equali-
sation stages, 8-48 times the optimisation time and
considerable increases in the financial cost.
8. ACKNOWLEDGEMENTS
The authors would like to thank Louis Fielder for the
question in a recent AES Conference in Denmark
sparking this paper’s content, Mr. Steve Fisher (SCV
London) for the original inspirational idea for the
optimiser and some of the measurements used in the
statistical analysis, Mr. Olli Salmensaari (Finnish
Broadcasting Corporation) for additional measure-
ments, Mr. Lars Morset (Morset Sound Development)
and Genelec Oy.
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