CoReAD - Cognitive Research in AD - Towards a model determining cognitive load in audio described audio(-visual) products.

Bonnie Geerinck University of Antwerp

In recent decades, research into audio description (AD) has become increasingly popular and AD has been approached from a variety of perspectives. However, its cognitive dimension has not yet received the attention it deserves. Although recent technological innovations have made it possible to directly measure which cognitive effects audiovisual products have on the human mind, within the field of media accessibility a methodological framework to carry out this kind of experimental research is still lacking. 

In recent decades, research into audio description (AD) has become increasingly popular and AD has been approached from a variety of perspectives. However, its cognitive dimension has not yet received the attention it deserves. Although recent technological innovations have made it possible to directly measure which cognitive effects audiovisual products have on the human mind, within the field of media accessibility a methodological framework to carry out this kind of experimental research is still lacking. 

The primary aim of the CoReAD (‘Cognitive Research in AD’) project is to bridge this gap by creating a model that can help to analyse the cognitive load that audio described audiovisual products impose on the target audience. By doing this, the project paves a way for future cognitive research not only into audio description but also within the field of media accessibility in general. The insights that will be gathered from such research, can in turn result in the creation of audio descriptions that are better adapted to the needs and abilities of the target audience. This way, the CoReAD project is not only of academic value, but serves a practical purpose as well.

To achieve this overarching objective, the project is divided into three main stages. The first phase consists of identifying and classifying all possible ‘cognitive load influencing features’ (CLIFs) on audio described products such as films and TV series. This will be carried out through a targeted literature review. In the second phase a model of all CLIFs will be developed. This model will allow its user to determine what CLIFs are present in the AD, to decide how they affect cognitive load, and how and if this effect can be optimised. Finally, in the third phase the usefulness of the model will be tested in a small-scale pilot study, after which the model will be adapted based on the findings of this study.