8th Speech in Noise Workshop, 7-8 January 2016, Groningen

The role of working memory capacity in processing demand during speech comprehension

Dorothea Wendt(a)
Hearing Systems group, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, DK

Torsten Dau
Hearing Systems group, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, DK

Jens Hjortkjær(b)
Hearing Systems group, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, DK

(a) Presenting
(b) Attending

The relationship between working memory capacity (WMC) and processing demands was investigated in a group of listeners with normal hearing. Processing demands were measured with either subjective ratings of perceived effort, or with pupil dilations as a physiological correlate of processing effort. Both measures were tested in an audio-visual picture matching paradigm, where the participant’s task was to match a spoken sentence with a picture that was presented prior to the sentence. The paradigm was tested using either syntactically simple or complex sentence structures. Sentences were presented at low and high noise levels, where speech intelligibility was still high. It was found that a higher WMC of the participants was correlated with an increase in pupil dilation. This finding was consistent with the resource hypothesis stating that people with higher WMC allocate more available resources that are utilized in the task (e.g. van der Meer et al., 2010; Zekveld et al., 2010). Furthermore, it was found that those participants with a larger WMC reported speech comprehension to be less effortful than participants with a lower WMC. This finding is in line with the ease of language understanding (ELU) model, which predicts that people with more cognitive resources require lower processing demands to achieve similar or better performance than people with reduced resources (Rönnberg et al. 2003; 2008). Our two findings indicate that WMC is in different ways related to perceived effort and processing effort, respectively. The two metrics represent different, potentially independent, components of cognitive processing demands.

Last modified 2016-05-12 14:22:09