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Linear regression is commonly used in the audio industry to create objective measurement models that predict subjective data. For any model development, the measure used to evaluate the accuracy of the prediction is important. The most common of these assume a linear relationship between the subjective data and the prediction, though in the early stages of model development this is not always the case. Measures based on rank ordering (such as Spearman’s test), can alternatively be used. Spearman’s test, however, does not consider the variance of the subjective results. This paper presents a method of incorporating the subjective variance in the Spearman’s rank ordering test using Monte Carlo simulations and shows how this can be used to develop predictive models.
Author (s): Pearce, Andy; Brookes, Tim; Mason, Russell; Dewhirst, Martin
Affiliation:
University of Surrey, Guildford, Surrey, UK
(See document for exact affiliation information.)
AES Convention: 140
Paper Number:9515
Publication Date:
2016-05-06
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Session subject:
Perception
Permalink: https://aes2.org/publications/elibrary-page/?id=18214
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Pearce, Andy; Brookes, Tim; Mason, Russell; Dewhirst, Martin; 2016; Measurements to Determine the Ranking Accuracy of Perceptual Models [PDF]; University of Surrey, Guildford, Surrey, UK; Paper 9515; Available from: https://aes2.org/publications/elibrary-page/?id=18214
Pearce, Andy; Brookes, Tim; Mason, Russell; Dewhirst, Martin; Measurements to Determine the Ranking Accuracy of Perceptual Models [PDF]; University of Surrey, Guildford, Surrey, UK; Paper 9515; 2016 Available: https://aes2.org/publications/elibrary-page/?id=18214