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Record W4392788772 · doi:10.21848/asr.230137

A Study on Improving Speech Perception in Noise and Cognitive-Communication Abilities in Elderly Individuals Wearing Hearing Aids through Web-Based Auditory Training

2024· article· en· W4392788772 on OpenAlexaboutno aff
Hyo Sun Chung, Junghwa Bahng

Bibliographic record

VenueAudiology and Speech Research · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsAudiologyPsychologySpeech perceptionPerceptionNoise (video)CognitionMedicineComputer scienceArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Purpose: This study aimed to explore the impact of web-based auditory training on speech perception in noise and cognitive-communication abilities in elderly individuals wearing hearing aids. The focus was on addressing communication difficulties commonly experienced by this demographic.Methods: Twenty participants, with over 6 months of hearing aid use, were divided into a training group (undergoing 8 weeks of weekly 60-minute web-based auditory training) and a non-training group. The training program included tasks like listening to sentences in noise, short and long stories, sentence arrangement, and crossword quizzes. Various assessments, such as Korean Repeat and Recall Test and Brief test Cognitive-Communication Disorders evaluations, were conducted before and after training. The Korean version of Montreal Cognitive Assessment test served as a prescreening measure for cognitive impairments.Results: Significant improvements were observed in the training group’s speech perception in noise, recall, and cognitive-communicative abilities post-training. Conversely, the non-training group showed no statistically significant differences.Conclusion: The findings suggest that web-based auditory training holds promise for enhancing cognition and communication in elderly hearing aid users. Future studies could further explore the comparative effectiveness of auditory training by categorizing participants into face-to-face, remote, and hybrid groups. This research contributes valuable insights into addressing communication challenges in the aging population through innovative training methods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.413
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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