The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Automatic lipreading by optical‐flow analysis
Abstract
While the acoustic signal is the primary cue in human speech recognition, the visual cue is also very useful, especially when the acoustic signal is distorted. A computer system is developed for automatic recognition of continuously spoken words by using only visual data. The velocity of lip motions may be measured from optical flow data which allows muscle action to be estimated. Pauses in muscle action result in zero velocity of the flow and are used to locate word boundaries. The pattern of muscle action is used to recognize the spoken words. In limited experiments involving the recognition of digits, it appears that the visually derived patterns of muscle action are stable for multiple utterances of the same word. Even across speakers the patterns are so similar that speaker‐independent recognition is possible. An overall accuracy including word spotting and recognition of approximately 70 percent is obtained across for continuously spoken test samples from three speakers.
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.
Integrity signals
Registry
Cites
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.
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
Hearing lips and seeing voices
MCGURK, H., & MACDONALD, J. (1976) · Nature · doi:10.1038/264746a0 · Cited by 6,183
Ekman, P., & Friesen, W. V. (2019) · PsycTESTS Dataset · doi:10.1037/t27734-000 · Cited by 6,019
Cited by
Audio-visual speech modeling for continuous speech recognition
Dupont, S., & Luettin, J. (2000) · IEEE Transactions on Multimedia · doi:10.1109/6046.865479 · Cited by 598
Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527
Lipreading With Local Spatiotemporal Descriptors
Zhao, G., Barnard, M., & Pietikainen, M. (2009) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2009.2030637 · Cited by 309
Automated facial expression recognition based on FACS action units
Lien, J. J., Kanade, T., Cohn, J. F., & Li, C.-C. (2002) · Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1998.670980 · Cited by 226
Metadata
- Authors
- Mase, K., & Pentland, A.
- Venue
- Systems and Computers in Japan
- Publisher
- Wiley
- Published
- 1991-01
- Volume
- 22
- Issue
- 6
- Pages
- 67-76
- ISSN
- 0882-1666 (ISSN-L)
- 1520-684X
- OpenAlex
- W1549662771
- Cited by
- 165
- References
- 2
- FWCI
- 5.78
- 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: Automatic lipreading by optical‐flow analysis. https://app.cochat.ai/papers/10.1002/scj.4690220607
- The paper
- Mase, K., & Pentland, A. (1991). Automatic lipreading by optical‐flow analysis. Systems and Computers in Japan. https://doi.org/10.1002/scj.4690220607
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.
