Implementation of MOS-transformation to be used with Rank based statistical techniques.
The rank correlation coefficients and the ranked-based statistical tests (as a subset of non-parametric techniques) might be misleading when they are applied to subjectively collected opinion scores. Those techniques assume that the data is measured at least at an ordinal level and define a sequence of scores to represent a tied rank when they have precisely an equal numeric value.
In this paper, we show that the definition of tied rank, as mentioned above, is not suitable for Mean Opinion Scores (MOS) and might be misleading conclusions of rank-based statistical techniques. Furthermore, we introduce a method to overcome this issue by transforming the MOS values considering their 95% Confidence Intervals. The rank correlation coefficients and ranked-based statistical tests can then be safely applied to the transformed values. We also provide open-source software packages in different programming languages to utilize the application of our transformation method in the quality of experience domain.
We provide implementation of our transformation method for MATLAB, Python and R.
Add the directory src/MATLAB to your MATLAB search path.
mos = [3.8,3.1];
ci = [0.8, 0.6];
expected_rank = [1.5,1.5];
new_rank = transform_mos(mos,ci); You can use the source code (src/pythonR) or install the package from pypi
pip install subjective-testInput the corresponding function and use it:
from subjective_test.utilities import transform_mos
mos = [4.5, 3, 2.5]
ci = [0.5, 0.2, 0.5]
t = transform_mos(mos, ci)
# expected_rank = [3, 1.5, 1.5]You can use the source code (src/R) or install the package from CRAN:
install.packages("transformmos")Input the corresponding function and use it:
library(transformmos)
mos <- c(1.1, 4, 5, 2, 3, 1.2, 4)
ci <- c(0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1)
new_rank <- transform_mos(mos,ci)
# expected <- c(1.5, 5.5, 7, 3, 4, 1.5, 5.5)Babak Naderi, babak.naderi[at]tu-berlin.de | bnaderi9[at]gmail.com
Naderi B, Möller S. Transformation of Mean Opinion Scores to Avoid Misleading of Ranked based Statistical Techniques Twelfth International Workshop on Quality of Multimedia Experience (QoMEX). IEEE, 2020.
MIT License
Copyright 2020 (c) Dr. Babak Naderi.
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