Benefits of Auditory Training with an Open-Set Sentences-in-Babble-Noise

Author:

Barda Ayelet1,Shapira Yair1,Fostick Leah2ORCID

Affiliation:

1. Department of Health Management, Ariel University, Ariel 40700, Israel

2. Department of Communication Disorders, Auditory Perception Lab in the Name of Laurent Levy, Ariel University, Ariel 40700, Israel

Abstract

Auditory training (AT) has limited generalization to non-trained stimuli. Therefore, in the current study, we tested the effect of stimuli similar to that used in daily life: sentences in background noise. The sample consisted of 15 Hebrew-speaking adults aged 61–88 years with bilateral hearing impairment who engaged in computerized auditory training at home four times per week over a two-month period. Significant improvements were observed in sentences comprehension (Hebrew AzBio (HeBio) sentences test) with both four-talker-babble-noise (4TBN) and speech-shaped-noise (SSN) and in words comprehension (consonant-vowel-consonant (CVC) words test), following one month of AT. These improvements were sustained for two months after completing the AT. No evidence of spontaneous learning was observed in the month preceding training, nor was there an additional training effect in the additional month. Participants’ baseline speech perception abilities predicted their post-training speech perception improvements in the generalization tasks. The findings suggest that top-down generalization occurs from sentences to words and from babble noise to SSN and quiet conditions. Consequently, synthetic training tasks focusing on sentence-level comprehension accompanied by multi-talker babble noise should be prioritized. Moreover, an individualized approach to AT has demonstrated effectiveness and should be considered in both clinical and research settings.

Funder

Ariel University’s Center for Aging Studies

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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