Evidence map›Paper›PMID 40407673›Full record

ArticleAudiology research2025

Preliminary Investigation of a Novel Measure of Speech Recognition in Noise.

Linda Thibodeau, Emma Freeman, Kristin Kronenberger, Emily Suarez, Hyun-Woong Kim, Shuang Qi, Yune Sang Lee

Abstract read
In one paragraph

Article in Audiology research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Linda ThibodeauDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Emma FreemanDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Kristin KronenbergerDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Emily SuarezDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Hyun-Woong KimDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Shuang QiDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0003-0030-4680
Yune Sang LeeDepartment of Speech, Language, and Hearing, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PURPOSE: The aim of this study was to investigate the use of an online test of speech processing in noise in listeners with typical hearing sensitivity (TH, defined as thresholds ≤ 25 dB HL) who were asked to determine the gender of the subject in sentences that were presented in increasing levels of continuous and interrupted noise. STUDY SAMPLE: Participants with self-reported TH (N = 153, ages 18-39 years, mean age = 20.7 years) who passed an online hearing screening were invited to complete an online questionnaire. DATA COLLECTION AND ANALYSIS: Participants completed a sentence recognition task under four SNRs (-6, -9, -12, and -15 dB), two syntactic complexity settings (subjective-relative and objective-relative center-embedded), and two noise types (interrupted and continuous). They were asked to listen to 64 sentences through their own headphones/earphones that were presented in an online format at a user-selected comfortable listening level. Their task was to identify the gender of the person performing the action in each sentence.

Indexed as

auditory trainingaural rehabilitationhearing testssignal-to-noise ratiospeech recognitionsyntactic complexity

Identifiers

PMID40407673
PMCPMC12101244

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.