ArticleThe Journal of the Acoustical Society of America2021
Role of semantic context and talker variability in speech perception of cochlear-implant users and normal-hearing listeners.
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 12 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Pooled it
- Effect of Speaking Rate and Sentence Context on Comprehension and Recognition Memory of Degraded Speech.Journal of speech, language, and hearing research : JSLHR · 2026Article
- The representation of speech conversations in the human auditory cortex: role of social and semantic factors.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Context effects for degraded speech: Effects of age, preceding or subsequent contextual cues, and signal-to-noise ratio.The Journal of the Acoustical Society of America · 2025Article
- Evaluating the role of age on speech-in-noise perception based primarily on temporal envelope information.Hearing research · 2025Article
- Testing the role of temporal coherence on speech intelligibility with noise and single-talker maskers.The Journal of the Acoustical Society of America · 2024Article
- How to vocode: Using channel vocoders for cochlear-implant research.The Journal of the Acoustical Society of America · 2024Article
- Lexical effects on talker discrimination in adult cochlear implant usersa).The Journal of the Acoustical Society of America · 2024Article
- Development of a Sentence Verification Task to Measure Speech Comprehension and Listening Effort in Cochlear Implant Users.Journal of speech, language, and hearing research : JSLHR · 2023Article
- Effortful Listening Despite Correct Responses: The Cost of Mental Repair in Sentence Recognition by Listeners With Cochlear Implants.Journal of speech, language, and hearing research : JSLHR · 2022Article
- Visualization of Speech Perception AnalysisFrontiers in neurology · 2021Article
- Repairing Misperceptions of Words Early in a Sentence is More Effortful Than Repairing Later Words, Especially for Listeners With Cochlear Implants.Trends in hearingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
This study assessed the impact of semantic context and talker variability on speech perception by cochlear-implant (CI) users and compared their overall performance and between-subjects variance with that of normal-hearing (NH) listeners under vocoded conditions. Thirty post-lingually deafened adult CI users were tested, along with 30 age-matched and 30 younger NH listeners, on sentences with and without semantic context, presented in quiet and noise, spoken by four different talkers. Additional measures included working memory, non-verbal intelligence, and spectral-ripple detection and discrimination. Semantic context and between-talker differences influenced speech perception to similar degrees for both CI users and NH listeners. Between-subjects variance for speech perception was greatest in the CI group but remained substantial in both NH groups, despite the uniformly degraded stimuli in these two groups. Spectral-ripple detection and discrimination thresholds in CI users were significantly correlated with speech perception, but a single set of vocoder parameters for NH listeners was not able to capture average CI performance in both speech and spectral-ripple tasks. The lack of difference in the use of semantic context between CI users and NH listeners suggests no overall differences in listening strategy between the groups, when the stimuli are similarly degraded.
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Registered trials
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.