When moving the sliders on a graphic equaliser, I never really have a clue about how to optimise the settings -even in general, let alone for each piece of music. This is partly because my ears aren’t particularly musically attuned but also because the variables seem to have effects which aren’t independent of each other. It would be tough enough to optimise the sound created even if they were.
Today’s invention is a way to achieve ‘optimal’ settings by relying on the opinions of many listeners ie crowd sourcing the equaliser sliders’ positions.
Every time someone felt they could tune their sound card to perform better, their settings for that card and the music they were listening to would be recorded by their browser and relayed to a central server. Here, the data from many expert listeners could be amassed and statistically analysed for the benefit of the less musically gifted.
When a piece was later being played on a networked system, the option would be provided to use one of a small range of the equaliser settings eg a) those of various celebrities, b) the average of all listeners, c) the choice of the recording artists themselves or even d) the settings adopted by the most discriminating of audiophiles.