Exploring audiovisual speech perception in monolingual and bilingual children in Uzbekistan
Bibliographic record
Abstract
This study aimed to investigate the development of audiovisual speech perception in monolingual Uzbek and bilingual Uzbek-Russian-speaking children, focusing on the impact of language experience on audiovisual speech perception and the role of visual phonetic (i.e. mouth movements corresponding to phonetic/lexical information) and temporal (i.e. timing of speech signals) cues.Three hundred twenty-one children in Tashkent, Uzbekistan, between the ages of 4 and 10 years discriminated /ba/ and /da/ syllables across three conditions: auditory-only, audiovisual phonetic (i.e., the sound accompanied by mouth movements), and audiovisual temporal (i.e, sound onset/offset accompanied by mouth opening/closing). Effects of modality (audiovisual phonetic, audiovisual temporal, or audio-only cues), age, group (monolingual vs. bilingual), and their interactions were tested using a Bayesian regression model.Participants performed better in the audiovisual phonetic modality compared to the auditory modality. However, no significant difference between monolingual and bilingual children was observed across all modalities. This finding stands in contrast with earlier studies. We attribute the contrasting findings of our study and the existing literature to the cross-linguistic similarity of the language pairs involved. When the languages spoken by bilinguals exhibit substantial linguistic similarity, there may be an increased necessity to disambiguate speech signals, leading to a greater reliance on audiovisual cues. The limited phonological similarity between Uzbek and Russian might have minimized bilinguals’ need to rely on visual speech cues, contributing to the lack of group differences in our study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".