Sound Quality Predition

In almost all areas that the AES is involved with, sound quality is of paramount importance. Physical measurements often only tell part of the story; perceptual quality judgments made by human assessors are the gold standard. There’s been a great deal of work on listening test methodologies and statistical testing to ensure that perceptual measurements are reliable and consistent. However, performing such tests is expensive, time consuming, and requires expertise. Consequently, researchers in industry and academia have worked on developing objective models for the prediction of sound quality (and of important aspects of sound perception such as loudness or speech intelligibility). These prediction models enable quick, repeatable measurements to be made, whilst maintaining perceptual validity.

The resources presented below provide an introduction to the field of sound quality prediction. They include journal, conference, and convention papers and videos describing the training, testing, and application of models; links to profiles of relevant groups and individuals in the AES; and links to external resources.

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Sound Quality Predition

Curators

Jon Francombe is a research fellow in the Institute of Sound Recording, University of Surrey. His research background is in perceptual audio quality evaluation. He has worked on methods for understanding listener perception of novel audio technologies (including personal sound zones and new spatial audio reproduction methods), and producing and developing predictive models of important perceptual attributes.
Sound Quality Predition
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