Set-size procedures for controlling variations in speech-reception performance with a fluctuating masker

Joshua G.W. Bernstein*, Van Summers, Nandini Iyer, Douglas S. Brungart

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Adaptive signal-to-noise ratio (SNR) tracking is often used to measure speech reception in noise. Because SNR varies with performance using this method, data interpretation can be confounded when measuring an SNR-dependent effect such as the fluctuating-masker benefit (FMB) (the intelligibility improvement afforded by brief dips in the masker level). One way to overcome this confound, and allow FMB comparisons across listener groups with different stationary-noise performance, is to adjust the response set size to equalize performance across groups at a fixed SNR. However, this technique is only valid under the assumption that changes in set size have the same effect on percentage-correct performance for different masker types. This assumption was tested by measuring nonsense-syllable identification for normal-hearing listeners as a function of SNR, set size and masker (stationary noise, 4- and 32-Hz modulated noise and an interfering talker). Set-size adjustment had the same impact on performance scores for all maskers, confirming the independence of FMB (at matched SNRs) and set size. These results, along with those of a second experiment evaluating an adaptive set-size algorithm to adjust performance levels, establish set size as an efficient and effective tool to adjust baseline performance when comparing effects of masker fluctuations between listener groups.

Original languageEnglish
Pages (from-to)2676-2689
Number of pages14
JournalJournal of the Acoustical Society of America
Volume132
Issue number4
DOIs
StatePublished - Oct 2012
Externally publishedYes

Fingerprint

Dive into the research topics of 'Set-size procedures for controlling variations in speech-reception performance with a fluctuating masker'. Together they form a unique fingerprint.

Cite this