Lipreading as a communication strategy to enhance speech recognition in individuals with hearing impairment: a scoping review
Bibliographic record
Abstract
PURPOSE: This article explores the existing research evidence on the potential effectiveness of lipreading as a communication strategy to enhance speech recognition in individuals with hearing impairment. METHODS: A scoping review was conducted, involving a search of six electronic databases (MEDLINE, Embase, Web of Science, Engineering Village, CINAHL, and PsycINFO) for research papers published between January 2013 and June 2023. This study included original research papers with full texts available in English, covering all study designs: qualitative, quantitative, and mixed methods. These studies had to examine lipreading as an approach to enhance speech recognition and involve metrics of word recognition accuracy or speech recognition performance. RESULTS: This review identified a total of 18 articles that met the inclusion criteria. The research evidence is limited to descriptive analysis of lipreading to enhance speech recognition. Most of the studies focused on audiological, computational and hearing-related aspects. The features supporting the effectiveness of lipreading were found to be related to (a) Speaker: The accurate lip movements and the role of facial expressions; (b) Person lipreading: Skills and personal characteristics; (c) Technology to capture and/or support lipreading, and (d) Environmental and contextual factors. CONCLUSION: Findings of this review indicate that lipreading can be an effective approach to enhancing speech recognition of people with hearing disabilities, giving attention to a combination of the factors related to individuals with hearing impairment, speaker, environment, and technology. Further research is required to investigate interaction among these factors to inform development of efficient lipreading systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".