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TASLP
2016

Bayesian Analysis of Phoneme Confusion Matrices

4 years 3 months ago
Bayesian Analysis of Phoneme Confusion Matrices
Abstract—This paper presents a parametric Bayesian approach to the statistical analysis of phoneme confusion matrices measured for groups of individual listeners in one or more test conditions. Two different bias problems in conventional estimation of mutual information are analyzed and explained theoretically. Evaluations with synthetic datasets indicate that the proposed Bayesian method can give satisfactory estimates of mutual information and response probabilities, even for phoneme confusion tests using a very small number of test items for each phoneme category. The proposed method can reveal overall differences in performance between two test conditions with better power than conventional Wilcoxon significance tests or conventional confidence intervals. The method can also identify sets of confusion-matrix cells that are credibly different between two test conditions, with better power than a similar approximate frequentist method.
Leijon Leijon, Gustav Eje Henter, Martin Dahlquist
Added 10 Apr 2016
Updated 10 Apr 2016
Type Journal
Year 2016
Where TASLP
Authors Leijon Leijon, Gustav Eje Henter, Martin Dahlquist
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