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    timing stats

    • Started by Jeff Hollocher
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    • Registered: 23-Jul-2006
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    Hi Shai, I was just thinking about the speculation concerning which types of movement are more important to stress when computing or manually forming an ideal layout. Someone asked earlier about the fact that you maximize pressing common letter combinations on the same hand as opossed to Dvorak's idea that the a more important thing to maximize is the alternation of the hands as we type. I'm not exactly sure on the subject, but I feel like things like that, in addition to other disputes could be settled by analyzing timing statistics of typical, home-row-adept, typers. Are there stats like this already analyzed and posted somewhere?

    Cheers and thanks!
    Jeff

    PS: This post was typed using Colemak!

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    • Shai
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    • Registered: 11-Dec-2005
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    There is some timing research done on Peter Klausler's evolved layout, however I found several very major flaws in the statistical analysis, which render the results statistically meaningless.

    Moreover, timing statistics are very dependant on the layout used and the associated muscle memory, finger size, finger flexibility and agility, keyboard dimensions, typing errors, hesitations, typing technique, etc. It's practically impossible to get statistically meaningful information by measuring timing.

    IMO, the hand alteration rate in Colemak is optimal, not too high and not too low. There is no clear concensus on the subject. See here for a discussion on hand alternation.

    The other major factors that affect speed are finger balance, same-finger ratio and finger distance. In all these criterias Colemak is very close to the theoretical limits. The nice thing about Colemak that it's also Easy to learn.

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    I don't think Peter Klausler did exactly what I'm suggesting. I should be more specific.

    Say that you had a little program to type sample of text into. The program would keep track of the time taken in between each key stroke. You could ask a bunch of people to type the text sample as quick as they could, and record the key delays. If you knew which keyboard layout the subjects used, you could map the pressed characters to the location of the pressed keys. That way, the data would be more relevant and much less dependent on the keyboard layout used. The data would vary for subjects with different muscle memory, finger size, etc. However, on average, I feel as though it would be meaningful.

    Hmm... it would also be good to normalize each user's timings. In other words, divide all of each user's timings by how long they took to type the entire text.

    There would be many key combos in which the hand movement is the same on two different layouts, but the associated letters are different. That means that the combo will, on average, have been practiced more or less for each layout due to the frequency of that pair of letters. If the typists are well practiced, and averages are taken, this difference would be less. In fact, if many different keyboard layouts were used, the averages would be even better.

    To resolve the specific case I mentioned in my initial post we would extract all timings associated with two keys pressed adjacent on the keyboard, next to each other in the same word, and pressed by the same hand. Perhaps there could be more restrictions as well. Then take the average. Then extract all timings associated with two keys pressed, one by each hand, pressed one immediately after the other, in the same word. If it's true that adjacently pressed keys happens faster than hand-alternatingly pressed keys, then the data may confirm it.

    Klausler says, "I constructed a complicated function that measures the amount of "work" needed to touch-type a given text with a given layout." He goes on to explain his made up function. If he instead recorded key timings and based his function on how fast people actually type, that would be really cool!

    Last edited by Jeff Hollocher (23-Jul-2006 05:46:46)
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    • Shai
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    Take a closer look at Klauser's third experiment, that's what he did. I personally don't place too much importance on hand alteration. Klauser's experiment page is very popular and it has been there for years and no one has volunteered yet to send keystroke timing data. That doesn't give me too much hope.

    If you're interested in doing the research on that topic, I suggest you'll use the work that Klauser already did.
    The flaws are in the statistical analysis kbstats.c are:
    * It takes into account the keypresses that are <2000ms. This limit should be changed to something much smaller, e.g. 400ms.
    * It takes into account even statistical data that only has one data sample. Any statistical data should have at least 16 data samples or should be discarded.
    * Moreover, the data should be gathered from many people using different keyboard layouts.

    Even if you did all that research, this varies quite a lot from person to person. Some people can more easily coordinate key presses between hands better than others, and all the other differences I mentioned above.

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    Awesome!  : )

    That's pretty cool! It does seem like a much lower keypress-time filter would do. And also, it seems like he could have analyzed the data from more perspectives, with more data, like you said. I like his idea... perhaps if I'm very bored one day, I'll modify it to keep zxcv where they are and give better ratings to qwerty-like layouts...

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