Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 342

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Auditory-visual speech recognition by hearing-impaired subjects: Consonant recognition, sentence recognition, and auditory-visual integration

Grant, Ken W., Walden, Brian E., Seitz, Philip F.·1998·The Journal of the Acoustical Society of America

Abstract

Factors leading to variability in auditory-visual (AV) speech recognition include the subject’s ability to extract auditory (A) and visual (V) signal-related cues, the integration of A and V cues, and the use of phonological, syntactic, and semantic context. In this study, measures of A, V, and AV recognition of medial consonants in isolated nonsense syllables and of words in sentences were obtained in a group of 29 hearing-impaired subjects. The test materials were presented in a background of speech-shaped noise at 0-dB signal-to-noise ratio. Most subjects achieved substantial AV benefit for both sets of materials relative to A-alone recognition performance. However, there was considerable variability in AV speech recognition both in terms of the overall recognition score achieved and in the amount of audiovisual gain. To account for this variability, consonant confusions were analyzed in terms of phonetic features to determine the degree of redundancy between A and V sources of information. In addition, a measure of integration ability was derived for each subject using recently developed models of AV integration. The results indicated that (1) AV feature reception was determined primarily by visual place cues and auditory voicing+manner cues, (2) the ability to integrate A and V consonant cues varied significantly across subjects, with better integrators achieving more AV benefit, and (3) significant intra-modality correlations were found between consonant measures and sentence measures, with AV consonant scores accounting for approximately 54% of the variability observed for AV sentence recognition. Integration modeling results suggested that speechreading and AV integration training could be useful for some individuals, potentially providing as much as 26% improvement in AV consonant recognition.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1121/1.422788

Cites

26 of 26 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 26 references

Cited by

See all 342

Metadata

Authors
Grant, K. W., Walden, B. E., & Seitz, P. F.
Venue
The Journal of the Acoustical Society of America
Published
1998-05-01
Volume
103
Issue
5
Pages
2677-2690
ISSN
  • 0001-4966 (ISSN-L)
  • 1520-8524
OpenAlex
W2020098907
Cited by
342
References
26
FWCI
11.26
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Auditory-visual speech recognition by hearing-impaired subjects: Consonant recognition, sentence recognition, and auditory-visual integration. https://app.cochat.ai/papers/10.1121/1.422788
The paper
Grant, K. W., Walden, B. E., & Seitz, P. F. (1998). Auditory-visual speech recognition by hearing-impaired subjects: Consonant recognition, sentence recognition, and auditory-visual integration. The Journal of the Acoustical Society of America. https://doi.org/10.1121/1.422788

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.