ArticleThe Journal of the Acoustical Society of America2020
Combining partial information from speech and text.
Article in The Journal of the Acoustical Society of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Recognition of Interrupted Speech, Text, and Text-Supplemented Speech by Older Adults: Effect of Interruption Rate.Journal of speech, language, and hearing research : JSLHR · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The current study investigated how partial speech and text information, distributed at various interruption rates, is combined to support sentence recognition in quiet. Speech and text stimuli were interrupted by silence and presented unimodally or combined in multimodal conditions. Across all conditions, performance was best at the highest interruption rates. Listeners were able to gain benefit from most multimodal presentations, even when the rate of interruption was mismatched between modalities. Supplementing partial speech with incomplete visual cues can improve sentence intelligibility and compensate for degraded speech in adverse listening conditions. However, individual variability in benefit depends on unimodal performance.
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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.