Integration of acoustic and visual speech signals using neural networks
Abstract
Results from a series of experiments that use neural networks to process the visual speech signals of a male talker are presented. In these preliminary experiments, the results are limited to static images of vowels. It is demonstrated that these networks are able to extract speech information from the visual images and that this information can be used to improve automatic vowel recognition. The structure of speech and its corresponding acoustic and visual signals are reviewed. The specific data that was used in the experiments along with the network architectures and algorithms are described. The results of integrating the visual and auditory signals for vowel recognition in the presence of acoustic noise are presented.>
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Some recently successful practice used weakly aligned image-text pairs to perform pretraining and achieve both competitive performance and zero-shot learning capability for image classification, image-text retrieval, and open-ended visual question answering.
“Some recently successful practice [9], [199], [205] used weakly aligned image-text pairs to perform pretraining, and achieve both competitive performance and zero-shot learning capability for image classification, image-text retrieval, and open-ended visual question answering, etc.”
From Multimodal learning with transformers: A survey (2023) · cites this paper as [205]
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- Authors
- Yuhas, B. P., Goldstein, M. H., & Sejnowski, T. J.
- Affiliations
- Johns Hopkins University (US)
- Venue
- IEEE Communications Magazine
- Published
- 1989-11
- Volume
- 27
- Issue
- 11
- Pages
- 65-71
- ISSN
- 0163-6804 (ISSN-L)
- OpenAlex
- W2151096985
- Cited by
- 209
- References
- 59
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 15 · 2023: 13 · 2022: 15 · 2021: 11 · 2020: 12 · 2019: 6 · 2018: 8 · 2017: 4 · 2016: 3 · 2015: 7 · 2014: 4 · 2013: 3 · 2012: 4
- FWCI
- 5.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Communications Magazine (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Keywords
- visual speech, vowel recognition, artificial neural networks, speech recognition, acoustic noise, multimodal speech processing
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.
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