And here is the last concept that I need to explain in regards to df-measurements.
The main beauty of df-metric is possibility to find/define the special point on df scale, which corresponds to some df level with real music signal. Achieving this low level of difference any audio device disappears from audio path and it's presence can not be discovered by means of listening tests. This is audio singularity level (s-level). At this level the amount of all possible distortions is so small that discovering/researching them makes no sense. Psychoacoustics does not work below this point. Thus the problem of delivering high quality audio can be turned into pure engineering task - to provide required level of accuracy for real music signal. And you need to control at consuming side only one easily measurable parameter - df level with that signal (or program simulation noise in many cases). All other audio measurements loose their power completely below s-level.
This concept has the reasoning of a higher ground. Music is created by author on production side. Warmth, harshness, openness, brightness, scene depth ... are the author's instruments. Playback devices are just a communication channel aimed to deliver all those characteristics of sound untouched. Having transparent audio path the hard work of both artists/musicians and audio engineers/producers will be clearly audible. Nothing prevents though to insert into this transparent audio path some DSP simulating all your favorite tube/vinyl distortions and performing thousand other processings for creative listening. But all this is only in addition to transparent path, on top of it.
Current level of technology in audio industry is more than sufficient for producing cheap consumer audio devices operating below the audio singularity level. Median of histogram on df-slides shows how far from this point a DUT is.
Hi Serge,
The promise of a simple metric like df is indeed enticing. In my mind there are two questions that I'd like to see answered:
1. Demonstrate that df metric is indeed correlated with perceived audio quality (I think you had some studies referenced on your site -- can you please link them and describe in more detail?) Is there a sufficient evidence that df is better correlated than, say THD or THD+N or other common metrics?
2. Is there a sufficient difference between the df metric and the RMS null difference as computed by DeltaWave (and, similar software like AudioDiffMaker)?
For #1, I can certainly add 'df' as a measurement to DeltaWave and make it available to let others run their own tests, once we determine that it's being computed accurately. But more important in my mind are the actual controlled studies that show real correlation. THD+N is indeed a poor metric for audibility of distortions, I've proven this to myself and others have as well. It seems THD+N at the levels measured using modern DACs and preamps, and even amps is low enough to not really be audible. Maybe other than for some specialized, single-ended triode or guitar amplifiers and similar devices where distortion is there by design.
For #2 it looks to me, after running only only a few tests that RMS difference, a global metric, is very closely correlated with df. The question is which is more accurate and better correlated with audibility. I see why df might be a better metric, but this needs to be properly tested to confirm since RMS difference has been measured and available for quite a while, as in the example of the DAC/ADC loop measurements on gearslutz website I linked previously.
