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Development of the Persian Listening in Spatialized Noise Sentence Test: A Preliminary Study Publisher



Hosseini Dastgerdi Z1 ; Gohari N2, 3 ; Yousefi A4 ; Rouhbakhsh N5
Authors

Source: Auditory and Vestibular Research Published:2025


Abstract

Background and Aim: Listening in Spatialized Noise Sentence (LiSN-S) is one of the auditory processing disorder test battery that specifically diagnose spatial processing disorders. This research aimed to develop The Persian version of the LiSN-S, for assessing auditory processing disorders in the Persian speakers’ population. Methods: The PLiSN-S test was developed based on its original Australian version. The speech stimuli were convolved with Head-Related Transfer Functions (HRTFs) to generate speech in the presence of spatialized noise. In total, 120 target sentences (consisting of five 1-3-syllable words) and competing stories were presented in four conditions. These included the Same Voice co-located condition (SV0°), Different Voice co-located condition (DV0°), Same Voice separated condition (SV±90°), and Different Voice separated condition (DV±90°). Then, data from 30 adults aged 18–23 with normal hearing were obtained. Results: The results from the normal-hearing subjects showed that the Speech Reception Threshold (SRT) scores, expressed as Signal to Noise Ratios (SNR), varied across the four conditions (SV0°, DV0° SV±90°, DV±90°) the highest and lowest SRTs belonged to the first and last conditions, respectively. The amount of advantage in all conditions was lower than in the previously published English versions. Conclusion: Considering the impact of spatial separation on the SRTs, PLiSN-S appears to be an effective tool for measuring spatial processing skills. © 2025 Tehran University of Medical Sciences. Published by Tehran University of Medical Sciences.
2. Spatial Hearing and Speech Understanding in Noise in Elderly, Hearing# Balance and Communication (2021)
3. Human Frequency Following Response Correlates of Spatial Release From Masking, Journal of Speech# Language# and Hearing Research (2019)
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