Spoken narrative comprehension for young adult listeners: effects of competing voices and noise

Abstract

Objective

To examine the influence of competing voices or noise on the comprehension of spoken narratives for young adults.

Design

First, an intelligibility assessment of the target narratives was conducted to establish a signal-to-noise ratio ensuring accurate initial speech recognition. Then, narrative comprehension for two target types (fixed and varied target talker) was measured in four listening conditions (quiet, one-talker speech, speech babble, speech-shaped noise). After hearing target narratives in each listening condition, participants completed a visual recognition memory task that assessed the comprehension of the narrative materials at three levels of representation (surface form, propositional, event model).

Study Sample

Seventy adults (18–32 years of age).

Results

Narrative comprehension results revealed a main effect of listening condition at the event model level, indicating poorer narrative memory of described situations for all noise conditions compared to quiet. Increased positive responses to thematically consistent but situationally “wrong” memory probes drove this effect. No other significant effects were observed.

Conclusion

Despite near-perfect speech recognition, background noise negatively influenced aspects of spoken narrative comprehension and memory. Specifically, noise did not disrupt memory for what was said (surface form and propositional memory), but only memory for what was talked about (event model memory).

Keywords:

• Spoken narrative comprehension
• memory
• background noise

Acknowledgements

We are thankful for our undergraduate and graduate research assistants. Their help with voice recordings and data collection during this project was invaluable. We are also grateful to Jessica Salley, Nardine Taleb, and Jessica Kong for their assistance during this project.

Disclosure statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.

Data availability statement

Stimulus materials and memory data are available from https://osf.io/pwamf/.

Notes

1 For written text, this is often referred to as the textbase level.

2 Often, speech babble maskers are produced with multiple unique voices. Here, we used one consistent voice to create this masker (see also Spahr et al. 2012 and Iyer et al. 2010). Perceptually, this still resulted in a babble noise, which can be accessed via our Open Science Framework page (see link in Data Availability Statement).

3 Also referred to as a norming study in the memory literature.

4 Planned recruitment for the varied target talker condition was 30 participants. However, data collection was stopped as a result of the coronavirus pandemic.

5 Although the Schmalhofer and Glavanov procedure uses signal detection theory to parse the levels of memory representation, it is not conventional to use responses to probes that were not actually presented to participants as the signal in this way (i.e., for propositional and event model recognition accuracy). Therefore, we also examine positive response proportions (i.e., the mean rates of responding “yes” to the four different probe types) in a separate analysis of these data.