Evidence map›Paper›PMID 34852602›Full record

ArticleThe Journal of the Acoustical Society of America2021

Older adult recognition error patterns when listening to interrupted speech and speech in steady-state noise.

Kimberly G Smith, Daniel Fogerty

Abstract read
In one paragraph

Article in The Journal of the Acoustical Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed.

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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

2 authors.

Kimberly G SmithDepartment of Speech Pathology and Audiology, University of South Alabama, 5721 USA Drive North, Alabama 36688, USA.
Daniel FogertyDepartment of Speech and Hearing Science, University of Illinois Urbana-Champaign, 901 S. Sixth St., Champaign, Illinois 61820, USA.

Funding

Maximizing speech recognition under adverse listening conditionsR01DC015465 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FOGERTY, DANIEL · 2016 to 2020
$1.6M
Maximizing Speech Recognition Under Adverse Listening ConditionsR03DC012506 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FOGERTY, DANIEL · 2012 to 2014
$313k
NIDCD NIH HHS R01 DC015465NIDCD NIH HHS R03 DC012506
6 · The paper itself

Abstract

This study examined sentence recognition errors made by older adults in degraded listening conditions compared to a previous sample of younger adults. We examined speech recognition errors made by older normal-hearing adults who repeated sentences that were corrupted by steady-state noise (SSN) or periodically interrupted by noise to preserve 33%, 50%, or 66% of the sentence. Responses were transcribed and coded for the number and type of keyword errors. Errors increased with decreasing preservation of the sentence. Similar sentence recognition was observed between SSN and the greatest amount of interruption (33%). Errors were predominately at the word level rather than at the phoneme level and consisted of omission or substitution of keywords. Compared to younger listeners, older listeners made more total errors and omitted more whole words when speech was highly degraded. They also made more whole word substitutions when speech was more preserved. In addition, the semantic relatedness of the substitution errors to the sentence context varied according to the distortion condition, with greater context effects in SSN than interruption. Overall, older listeners made errors reflecting poorer speech representations. Error analyses provide a more detailed account of speech recognition by identifying changes in the type of errors made across listening conditions and listener groups.

Indexed as

SpeechSpeech PerceptionAuditory PerceptionNoiseRecognition, Psychology

Identifiers

PMID34852602
PMCPMC8577864

What OpenQuestion holds

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Registered trials

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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.