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Math Help - T-Test: How to take into account data number for each population member?

  1. #1
    genetix
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    T-Test: How to take into account data number for each population member?

    Hello!

    I am evaluating statistical significance of improvements in accurracy in a speech recognition system as a response to changes within the acoustic models. I am comparing the mean recognition accuracy before and after the changes.

    As an input I've got pairs of "speaker - accuracy" or "word - accuracy" for both groups. As I am keeping speakers and vocabulary the same in both evaluations, I decided to use the t-test for dependent samples to find out if there is a significant change in mean accuracy or not.

    There is still one thing, I wonder about: The standard t-test for dependent populations does not seem to be able to take into account the number of test samples that I have either per vocabulary item or per speaker. If I evaluate on a "by speaker"-basis, then the t-test makes no difference if I've got 20 or 50 utterances per speaker. If I evaluate on a "by vocabulary item"-basis, there is no dependence on the number of evaluation speakers.
    As I evaluate 20 speakers but 100 utterances per speaker the significance is usually much higher if I run the t-test based on vocabulary items instead of speakers.

    Is there another test or a modification of the t-test which takes this information into account? For each utterance I've got the information if it was recognized correctly or incorrectly. So I cannot run the t-test directly on the utterances because I need an interval scale for that and not only a binary decision. Is there a way to test on speakers and vocabulary items separately and obtain a better information about significance from those two results?

    I'd be glad if anyone could help me as my knowledge of statistics is rather limited...

    thank you in advance,
    Anja
    Last edited by genetix; June 6th 2005 at 05:45 PM.
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  2. #2
    hpe
    hpe is offline
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    This looks like an ANOVA (Analysis of Variance) problem. A decent introduction is here.
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