How well calibrated is your monitor? My wife recently had a “That’s not what I wanted!” experience after discovering that the brightness levels which are optimal for watching movies are not optimal for designing artwork which looks the same after printing. Unless you’ve done some careful tweaking you might not be learning the colors you think you’re learning.
For sound generation, what operating system are you using? Alsa (at least on Ubuntu 13.10) comes with “speaker-test”, a command line program which can be used to play specified frequency sine waves, and alsa itself can be configured to allow you to save sound output to files.
..And that’s pretty much the story of how at work we ended up with a hideous orange conference table instead of the nice warm brown our department chair envisioned
Unless you’ve done some careful tweaking you might not be learning the colors you think you’re learning.
Calibration is something I don’t learn, at the moment I can more about fine color distinction.
For sound generation, what operating system are you using? Alsa (at least on Ubuntu 13.10) comes with “speaker-test”, a command line program which can be used to play specified frequency sine waves, and alsa itself can be configured to allow you to save sound output to files.
I use windows, but I might write a script and run it on a linux computer to get files, I will think about it.
Calibration is something I don’t learn, at the moment I can more about fine color distinction.
You’re teaching yourself to associate labels (e.g. “midnight blue”) with particular colors.
You seem to be doing the colors on your monitor and I doubt your monitor is color-calibrated. This implies that you’re looking at a somewhat-randomized version of a true color. Your monitor also has a limited gamut (the set of colors that it can display) and for some monitors the gamut is very limited to the extent that they have to simulate some colors by dithering. Most uncalibrated monitors are too bright and too blue.
Basically, display of proper colors on a screen is complicated and you must take active steps (e.g. color calibration) to make it happen.
You’re teaching yourself to associate labels (e.g. “midnight blue”) with particular colors.
Actually the css label is “midnightblue” without a space. For my purposes I don’t think it’s a problem to treat the word true as meaning whatever the hardware interprets it too mean.
I want to get better at precision of color distinction. Having accurate labels is secondary.
I don’t think it’s a probably to treat the word true as meaning whatever the hardware interprets it too mean
Your sentence doesn’t make sense, but keep in mind that we’re talking about what your local, particular, individual hardware interprets it to mean. My hardware (my screen) will likely interpret it differently. Screens of random people will interpret it differently again.
Also a lot of LCD screens use what’s known at TN (twisted nematic) panels and the great majority of them are 6-bit panels, that is, they drive pixels at only 2^6 = 64 levels. So, for example, they can only show you 63 levels of blue (0 is off/black) even though the standard software treatment of color is 8 bits per primary for 256 levels. The TN screens mitigate this problem through dithering.
Human vision is highly adaptive to ambient light, in particular its color temperature. We perceive colors differently in the sunlight, in the shade, or under a tungsten lamp. And these are full-spectrum light sources. Fluorescent lights are not, they have spikes and voids in their spectrum and that affects certain colors under them as well.
Yes, there should have been the word “problem” when I wrote the word “probably”.
As I said, it’s complicated.
I know that human vision is complicated.
I however also know my bit about measurement theory. The important thing isn’t that a measurement is “true” but that that it has features like sensitivity and specificity. Accuracy and precision are other words to speak about measurements.
When dealing with a complex subject the important thing is whether your map of reality is good enough for the purpose for which you want to use it. I think the way my computer models colors is good enough to produce a valid training effect that helps me to get better at distinguishing colors.
I could create a randomly generated filtered deck out of 100 mature Anki color cards and test it at the computer of someone else and see whether the particularities of my specific computer monitor produce a problem. It’s a question that has an empiric answer and in a year when I have put more training into the colors I probably will do something like that. At the moment I have one day 70% correct cards and the next day 85% right cards, so it’s not stable enough for good test.
My notebook has a slightly different color profile than my 24″ monitor. Switching between the two doesn’t produce issues I can perceive. It doesn’t feel like everything is suddenly wrong. My brain seems to be able to make the necessary adjustments that I can still answer the cards correctly.
Let’s use meatspace examples. Do you want to be able to look at a wall and say “this is color X”? Do you want to to be able to look at two walls side by side and say “These are different colors”? Do you want to be able look at a wall, look at another wall the next day and say “This is the same color as I saw yesterday”?
Being able to answer the question: What color is this isn’t very useful. It’s not what separates the person who rather wants to be deaf from the person who rather wants to be deaf. I want is a cure for my partial blindness. I want to perceive more bits of information through the visual channel.
I don’t care for ‘is’ or ‘true’. I’m post- aristotelean. To quote the constructivist Heinz von Foerster: Truth is the invention of a liar. Just in case you think, I’m off-topic, I’m not. Those Anki cards are a result of among other things reading Korzybski’s Science and Sanity.
To go back to questions I want to be able to notice if a website I visit changes their color scheme in a way that exchanges navy with midnightblue just as I’m now able to notice a change from red to green.
Given that your brain’s processing bandwidth is severely limited
I don’t think there a good reason to believe that. I think quite often the limiting factor is time spent in deliberate practice and not lack of neurons or similar hardware problems.
How well calibrated is your monitor? My wife recently had a “That’s not what I wanted!” experience after discovering that the brightness levels which are optimal for watching movies are not optimal for designing artwork which looks the same after printing. Unless you’ve done some careful tweaking you might not be learning the colors you think you’re learning.
For sound generation, what operating system are you using? Alsa (at least on Ubuntu 13.10) comes with “speaker-test”, a command line program which can be used to play specified frequency sine waves, and alsa itself can be configured to allow you to save sound output to files.
..And that’s pretty much the story of how at work we ended up with a hideous orange conference table instead of the nice warm brown our department chair envisioned
Calibration is something I don’t learn, at the moment I can more about fine color distinction.
I use windows, but I might write a script and run it on a linux computer to get files, I will think about it.
You’re teaching yourself to associate labels (e.g. “midnight blue”) with particular colors.
You seem to be doing the colors on your monitor and I doubt your monitor is color-calibrated. This implies that you’re looking at a somewhat-randomized version of a true color. Your monitor also has a limited gamut (the set of colors that it can display) and for some monitors the gamut is very limited to the extent that they have to simulate some colors by dithering. Most uncalibrated monitors are too bright and too blue.
Basically, display of proper colors on a screen is complicated and you must take active steps (e.g. color calibration) to make it happen.
Actually the css label is “midnightblue” without a space. For my purposes I don’t think it’s a problem to treat the word true as meaning whatever the hardware interprets it too mean.
I want to get better at precision of color distinction. Having accurate labels is secondary.
Your sentence doesn’t make sense, but keep in mind that we’re talking about what your local, particular, individual hardware interprets it to mean. My hardware (my screen) will likely interpret it differently. Screens of random people will interpret it differently again.
Also a lot of LCD screens use what’s known at TN (twisted nematic) panels and the great majority of them are 6-bit panels, that is, they drive pixels at only 2^6 = 64 levels. So, for example, they can only show you 63 levels of blue (0 is off/black) even though the standard software treatment of color is 8 bits per primary for 256 levels. The TN screens mitigate this problem through dithering.
Human vision is highly adaptive to ambient light, in particular its color temperature. We perceive colors differently in the sunlight, in the shade, or under a tungsten lamp. And these are full-spectrum light sources. Fluorescent lights are not, they have spikes and voids in their spectrum and that affects certain colors under them as well.
As I said, it’s complicated.
Yes, there should have been the word “problem” when I wrote the word “probably”.
I know that human vision is complicated.
I however also know my bit about measurement theory. The important thing isn’t that a measurement is “true” but that that it has features like sensitivity and specificity. Accuracy and precision are other words to speak about measurements.
When dealing with a complex subject the important thing is whether your map of reality is good enough for the purpose for which you want to use it. I think the way my computer models colors is good enough to produce a valid training effect that helps me to get better at distinguishing colors.
I could create a randomly generated filtered deck out of 100 mature Anki color cards and test it at the computer of someone else and see whether the particularities of my specific computer monitor produce a problem. It’s a question that has an empiric answer and in a year when I have put more training into the colors I probably will do something like that. At the moment I have one day 70% correct cards and the next day 85% right cards, so it’s not stable enough for good test.
My notebook has a slightly different color profile than my 24″ monitor. Switching between the two doesn’t produce issues I can perceive. It doesn’t feel like everything is suddenly wrong. My brain seems to be able to make the necessary adjustments that I can still answer the cards correctly.
What do you mean by that?
Let’s use meatspace examples. Do you want to be able to look at a wall and say “this is color X”? Do you want to to be able to look at two walls side by side and say “These are different colors”? Do you want to be able look at a wall, look at another wall the next day and say “This is the same color as I saw yesterday”?
Being able to answer the question: What color is this isn’t very useful. It’s not what separates the person who rather wants to be deaf from the person who rather wants to be deaf. I want is a cure for my partial blindness. I want to perceive more bits of information through the visual channel.
I don’t care for ‘is’ or ‘true’. I’m post- aristotelean. To quote the constructivist Heinz von Foerster: Truth is the invention of a liar. Just in case you think, I’m off-topic, I’m not. Those Anki cards are a result of among other things reading Korzybski’s Science and Sanity.
To go back to questions I want to be able to notice if a website I visit changes their color scheme in a way that exchanges navy with midnightblue just as I’m now able to notice a change from red to green.
Ah. Well, this is useful to know.
Given that your brain’s processing bandwidth is severely limited I think it’s mostly an issue of controlling your attention but experimenting is good.
I don’t think there a good reason to believe that. I think quite often the limiting factor is time spent in deliberate practice and not lack of neurons or similar hardware problems.