The development of the Listening in Spatialized Noise – Universal Test (LiSN-U) and preliminary evaluation in English-speaking listeners

Sharon Cameron, Kiri Trengove Mealings*, Nicky Chong-White, Taegan Young, Harvey Dillon

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Objective: To create a language independent version of the Listening in Spatialised Noise - Sentences test (LiSN-S) and evaluate it in an English-speaking population. Design: Test development and normative data collection. LiSN-Universal (LiSN-U) targets consisted of CVCV pseudo-words (e.g. /mupa/). Two looped distracter tracks consisted of CVCVCVCV pseudo-words. The listener's task was to repeat back the target pseudo-words. Stimuli were presented over headphones using an iPad. Speech reception thresholds were measured adaptively. In the co-located condition all stimuli came from directly in front. In the spatially-separated condition the distracters emanated from +90° and -90° azimuth. Perceived location was manipulated using head-related transfer functions. Spatial advantage was calculated as the difference in dB between the co-located and spatially separated conditions. Study samples: Stimulus intelligibility data were collected from 20 adults. Normative data were collected from native English speakers (23 adults and 127 children). Results: Children's spatially separated, co-located, and spatial advantage results improved significantly with age. Spatial advantage was 4-6 dB larger in the LiSN-U than LiSN-S depending on age group. Conclusion: Whereas additional research in non-native English populations is required, the LiSN-U appears to be an effective tool for measuring spatial processing ability.

Original languageEnglish
Pages (from-to)263–271
Number of pages9
JournalInternational Journal of Audiology
Volume59
Issue number4
Early online date13 Nov 2019
DOIs
Publication statusPublished - Apr 2020

Keywords

  • auditory processing disorder
  • spatial processing disorder
  • diagnostic tools
  • speech perception

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