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American Journal of Audiology Vol.15 81-91 June 2006. doi:10.1044/1059-0889(2006/010)
© American Speech-Language-Hearing Association

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Research and Technology | Articles

Comparison of Performance on the Hearing in Noise Test Using Directional Microphones and Digital Noise Reduction Algorithms

Stacie Nordrum, Susan Erler, Dean Garstecki and Sumitrajit Dhar

Northwestern University, Evanston, IL

Contact author: Sumit Dhar, Northwestern University, 2240 Campus Drive, Evanston, IL 60208-2952. Email: s-dhar{at}northwestern.edu

PURPOSE: Difficulty understanding speech in background noise is one of the most common complaints of hearing aid users. In modern hearing aids, directional microphones (d-mics) are considered the method of choice in improving signal-to-noise ratio, with demonstrated improvement in speech-perception-in-noise tasks. On the other hand, digital noise reduction (DNR) algorithms, in commercially available products, are considered to provide comfort but not significant assistance in improving speech perception in noise. In practice, these 2 technologies are often used in conjunction, but few studies have evaluated their interaction and the resultant effect on speech perception in noise. The purpose of this study was to evaluate the effect on speech performance of using d-mics and DNR in isolation as well as in conjunction in the presence of background noise.

METHOD: This study evaluates the performance of 16 experienced adult hearing aid users on the Hearing in Noise Test when each technology was activated independently and then simultaneously in 4 commercially available hearing aids.

RESULT: Approximately 50% of our participants performed better with both d-mics and DNR activated in conjunction, while the other 50% performed best in the d-mic-only condition. When considering statistically significant differences in performance only, a reduction or improvement in performance was observed in 17% and 14% of the conditions, respectively.

CONCLUSION: A direction for further research would be to identify predictive variables that could help the audiologist determine an individual's preference a priori.

Key Words: speech in noise, directional microphones, digital noise reduction algorithms







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