The only ''definitive'' answer in this Subjective world is...

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It was too long ago I did the tests... but agree the odd would be the one to key off of.

But with a good margin for error... like X10 reduction... I have assumed as my goal in designs or products I would purchase to be .001% thd to be assured of less than detectable for the entire system

It can be done today.... only with newest opamps and/or designs. But that still leaves the speakers and power amp as the weak links in the playback portion of the chain. Acoustic recordings would start with the mic preamp.... same problem... as speaker... microphone is limiting factor. It would be good to have an entire recording to playback chain measured... taking signal from mic to mixer to recorder thru mastering thru cd thru playback... what % distortion does the entire system of components add up to. Most likely would be above 0.1% is my guess. Newer almost all digital might offer best way to get entire system sounding more 'real'. Mic to ADC and at home DAC to digital amp. Leaves just mic and speaker as the limiting factor. They need to do better then.



--Richard
 
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Maybe a good idea to include a cognitive psychologist in a listening test research team.
Dr. Lee has a degree in experimental psychology, so our procedures were well controlled.
Maybe it is as you seem to be saying, the problem is not that we can't devise better distortion metrics and also make skilled listening much more reliable, the problem is that nobody is interested in doing it.
Nobody is interested because those who have studied it find no advantage to better understanding it. As far as loudspeakers go, just stop worrying about nonlinear distortion. There is so much linear distortion that the nonlinear stuff just doesn't matter.

If so, I could see there might not be commercial interest, but the area seems ripe for academic research. Just need to find a grant funding source with interest in making progress. Perhaps a rich audiophile.

Academics, like Lidia, don't do "academic" studies. Someone needs to fund it and people don't fund projects whose results no one cares about.
 
Acoustic recordings would start with the mic preamp.... same problem... as speaker... microphone is limiting factor.

Earl is right mics and speakers have low order distortions in general that vanish with level. Presence peaks, radiation patterns,etc. (so called linear distortions) have far more to do with what you are presented than any non-linear distortion mechanisms. Mic pre-amps with vanishing distortion of any kind are trivial to design.

Earl you are showing your age, there are several software tools that have complex math totally integrated in a way you don't even have to think about it. I don't know anyone in the scientific community that uses Fortran anymore except for a very narrow class of problems. I don't know of any circuit simulators or CAD programs written in it.
 
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I suspect we could identify skilled listeners through measurements. The recent Hi Res listening test thread in the forum here produced some interesting results suggesting how to identify suitable people and how to make sure they maintain accuracy over time though repeated practice and testing.

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Seriously? Come on Mark, nothing of the sort happened. Unless you are of the view that those who couldn't hear a difference were the only ones not deluding themselves.
 
Earl you are showing your age, there are several software tools that have complex math totally integrated in a way you don't even have to think about it. I don't know anyone in the scientific community that uses Fortran anymore except for a very narrow class of problems. I don't know of any circuit simulators or CAD programs written in it.

It is my understanding that Intel keeps FORTRAN alive because so much of their internal modeling software is in FORTRAN. Other compilers may have complex ability today, but FORTRAN has had it since its inception (or shortly thereafter.) This means many more complex number subroutines of proven accuracy are available in FORTRAN than just about any other language. Circuit simulations and CAD programs have never pushed the limits of complex number capability.

I believe that all FEA software is still in FORTRAN, or vast parts of it. Clearly no one today uses only one language for a complex app. I use at least two always. I never try and interface FORTRAN to the user. This is always done in VB.Net
 
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Earl is right mics and speakers have low order distortions in general that vanish with level. Presence peaks, radiation patterns,etc. (so called linear distortions) have far more to do with what you are presented than any non-linear distortion mechanisms. Mic pre-amps with vanishing distortion of any kind are trivial to design.

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Low order and vanishing distortion at low levels? Distortion is quite high in many loudspeaker systems... multi-way. And at realistic playback level, many have audible issues... beyond freq response.

BTW - measuring up close to the driver with 1W is not realistic playback level ---- realistic levels further back in a large room even with high effec speakers needs 10-20W from my tests.


THx-RNMarsh
 
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This means many more complex number subroutines of proven accuracy are available in FORTRAN than just about any other language.

Maybe I'm misunderstanding you, yes massive FEA and other huge problems that benefit from parallelism and speed but I don't know of any complex functions not available to Mathematica, Matlab or Python (for instance). Could you name one?

Much of the algorithm development in the scientific community is done in non-compiled languages because the scientists time is more valuable than the C and Fortran coders.

The main programming language selected for the development of physics software applications in all four LHC experiments is C++, with some legacy algorithms written in FORTRAN, and Python is used in cases where a scripting language is more appropriate.

and from Intel itself

does a huge science project get the notice of the broader world like the announcement last week that gravitational waves have been discovered by LIGO. It has been likened to Galileo first looking through a telescope to the heavens.
What I did not know until yesterday was the impact that the Python programming language had on this project. The following email was sent to the Python community at large, thanking the community for the work we are doing with Python.
 
Could you name one?

For the fundamental intrinsic functions sure, many languages have complex functions, but in physics there are way more complex functions than any language has intrinsically. For example, say I wanted to know the complex eigenvalues for the Matheau Function. I can easily find existing subroutines that do this extremely obscure calculation in FORTRAN (I have these subroutines myself,) but I doubt that they exist in the public domain in Python. It's all about legacy.
 
For the fundamental intrinsic functions sure, many languages have complex functions, but in physics there are way more complex functions than any language has intrinsically. For example, say I wanted to know the complex eigenvalues for the Matheau Function. I can easily find existing subroutines that do this extremely obscure calculation in FORTRAN (I have these subroutines myself,) but I doubt that they exist in the public domain in Python. It's all about legacy.

Yes I realize now you are simply talking about existing canned software, the complex number aspect has nothing to do with that. I realize you tried the most hopelessly obscure thing you could think of.

Scilab is open source for Python http://www.fis.unipr.it/~coisson/Mathieu.pdf

Abstract—We review the full spectrum of solutions to the
Mathieu differential equation y
00 + [a − 2q cos(2z)]y = 0, and
we describe a numerical algorithm which allows a flexible
approach to the computation of all the Mathieu functions. We
use an elegant and compact matrix notation which can be
readily implemented on any computing platform. We give some
explicit examples (written in the programming language Scilab)
that provide a ready-to-use package for solving the Mathieu
differential equation and related applications in several fields.
 
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Scipy/Numpy have an enormous number of those wonderful obscure mathematical functions. As mentioned before, I'm betting they're mostly compiled c modules. Sometimes less easy to get at, but it's open source and widely, widely, widely adopted at the academic level, where naive, idealistic people still exist and share things that they spent a lot of time developing. :) And where massive computational horsepower isn't necessarily always available, so people get rather crazy about code optimization (plus there are speed competitions out there).

And there's nothing preventing one from bolting on some fortran code into the middle of a python script as needed.
 
Scipy/Numpy have an enormous number of those wonderful obscure mathematical functions. As mentioned before, I'm betting they're mostly compiled c modules. Sometimes less easy to get at

Scipy and Numpy are transparent you just load the modules and use the functions. Once I got used used to the rich set of capabilities in the function arguments I never went back, pages of code turns into paragraphs and you can just understand it by reading it. The Analog Discovery, for instance, uses a separately compiled C++ .dll and you have to keep track of C variable typing in the arguments and return values in some cases but the functions just appear when you load the module.

I wasn't trying to give anyone a hard time, just pointing out how far the open source folks have come. Scilab is just another example of a huge collaborative open source effort all of which I support.

The use of the term "public domain" here is problematic. Any algorithm described 100yr. ago is by definition in the public domain, patent protection has certainly expired and copyright does not cover ideas disclosed 100yr. ago and not the author's original work.
 
Markw4 said:
Sure, I understand there are other measurements techniques such as FFT, multi-tone IMD, etc., and I am using THD or the word distortion as a kind of shorthand for how we measure nonlinear distortion.
Using "THD" (which has a well defined meaning) when you actually mean 'nonlinear distortion measured via harmonic distortion' is not helpful to meaningful debate.

I would like to get into to what if anything is being found by trusted listeners that instrumentation tests may not be good at picking up.
Most of the evidence is that anything which can be genuinely heard can be measured, although that does not necessarily mean that it is usually measured. Meaningful tests have to be on the basis 'does this or this sound the same or different?' because as soon as you ask 'does this sound better than this?' you are getting into preferences, which are notoriously unhelpful if the aim is high-fidelity sound reproduction. In either case the test must be unsighted, as otherwise all sorts of bias come into effect - especially for those who fondly believe themselves to be free of bias.

gedlee said:
1) THD and IMD are meaningless measures of audible distortion
Do you actually mean "meaningless", or do you mean 'less meaning than some believe'? The fact that a carefully constructed signal with 20% THD can sound less distorted than another carefully constructed signal with much smaller THD does not prove that THD is "meaningless". It just shows that THD has be be treated with caution, especially when carefully constructed signals are being used. For most generally useful measures of almost anything it is possible to construct an artificial scenario which does not fit the measure and so gives misleading results.

AllenB said:
No. Conventional boxes and driver selections have some issues that cannot be managed by pointing a mic at them and crossing them flat.
I did not realise you were talking about speakers.
 
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