Effects of noise and working memory capacity on memory processing of speech for hearing-aid users

Abstract

Objectives: It has been shown that noise reduction algorithms can reduce the negative effects of noise on memory processing in persons with normal hearing. The objective of the present study was to investigate whether a similar effect can be obtained for persons with hearing impairment and whether such an effect is dependent on individual differences in working memory capacity. Design: A sentence-final word identification and recall (SWIR) test was conducted in two noise backgrounds with and without noise reduction as well as in quiet. Working memory capacity was measured using a reading span (RS) test. Study sample: Twenty-six experienced hearing-aid users with moderate to moderately severe sensorineural hearing loss. Results: Noise impaired recall performance. Competing speech disrupted memory performance more than speech-shaped noise. For late list items the disruptive effect of the competing speech background was virtually cancelled out by noise reduction for persons with high working memory capacity. Conclusions: Noise reduction can reduce the adverse effect of noise on memory for speech for persons with good working memory capacity. We argue that the mechanism behind this is faster word identification that enhances encoding into working memory.

Key Words::

• Hearing-aid
• free recall
• cognitive abilities
• working memory
• individual differences

Note

Acknowledgements

The authors would like to thank Ulrik Kjems from Oticon A/S, Smørum, Denmark, for his contribution of ideas regarding the noise reduction signal processing, René Burmand Johannesson from the Eriksholm Research Centre, Oticon A/S, Snekkersten, Denmark; and Mathias Hällgren from the Department of Technical Audiology, Linköping University, Sweden, for their technical support, and Tomas Bjuvmar from the Hearing Clinic, University Hospital, Linköping, Sweden, for his assistance in data collection.

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

Notes

1. The voice aligned compression (VAC) rationale can be classified as curvilinear wide-dynamic range compression that, compared to many other amplification strategies, provides less compression at high input levels and more compression at low input levels through lower compression kneepoints (varying between 30 and 40 dB SPL, depending on frequency region and amount of hearing loss).

This compression model is partly based on loudness data by Buus and Florentine (2001) and is intended to ensure improved sound quality without loss of speech intelligibility, rather than loudness compensation per se.