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Test of Listening Difficulties - Universal (Data set)

dataset
posted on 2024-05-28, 04:12 authored by Harvey DillonHarvey Dillon, Sharon CameronSharon Cameron, Shrutika GaikwadShrutika Gaikwad, Ponsuang Luengtaweekul, Jorg BuchholzJorg Buchholz

The Test of Listening Difficulties - Universal (ToLD-U) is designed to evaluate the understanding of speech in a noisy, reverberant environment, using sentences comprised of words that are familiar to children from age 5 up. The test is a realistic speech-in-noise test designed to be sensitive to several causes of difficulty understanding speech in noise. The test, conducted under headphones, simulates listening in a typically reverberant classroom. It comprises a frontal target talker speaking high-context sentences and six competing talkers at different apparent locations. The test is intended to be the first test used by audiologists (or speech pathologists) after pure tone hearing thresholds have been measures, if the person is reported to be having difficulty understanding speech in acoustically challenging situations. If the ToLD-U test indicates that the person's performance is outside the normal range of abilities for people of that age, then that is an indication that additional tests should be administered to discover whether the cause(s) lie in the domains of auditory processing (especially spatial processing disorder), cognition (especially memory and attention), language (especially cloze ability), recognition of individual speech sounds, or types of hearing loss that are not evident in the usual audiogram.

The data in this data set are the measured intelligibility scores for children and adults in Australia when listening to the Australian-accented version of ToLD-U, which was the first version created. These data are described more fully in the article by Dillon, Gaikwad, Cameron, Luengtaweekul, Buchholz & Cameron: Development of the Test of Listening Difficulties - Universal (ToLD-U) and Australian normative data in children and adults.

Also included is the statistics program, in R, that was used to analyse the data for that publication, which is currently under peer review.

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  • FAIR assessment completed
  • Institutional review completed

FAIR Self Assessment Summary

This text has been generated from a tool that has been adapted from the ARDC FAIR Assessment Tool Findable -------- Does the dataset have any identifiers assigned? Global Is the dataset identifier included in all metadata records/files describing the data? Yes How is the data described with metadata? Comprehensively (see suggestion) using a recognised formal machine-readable metadata schema What type of repository or registry is the metadata record in? Data is in one place but discoverable through several registries Accessible ---------- How accessible is the data? Publicly accessible Is the data available online without requiring specialised protocols or tools once access has been approved? Standard web service API (e.g. OGC) Will the metadata record be available even if the data is no longer available? Yes Interoperable ------------- What (file) format(s) is the data available in? In a structured, open standard, machine-readable format What best describes the types of vocabularies/ontologies/tagging schemas used to define the data elements? Standardised vocabularies/ontologies/schema without global identifiers How is the metadata linked to other data and metadata (to enhance context and clearly indicate relationships)? There are no links to other metadata Reusable -------- Which of the following best describes the license/usage rights attached to the data? Standard machine-readable license (e.g. Creative Commons) How much provenance information has been captured to facilitate data reuse? No provenance information is recorded

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