Lexical-perceptual integration influences sensorimotor adaptation in speech
Bibliographic record
Abstract
A combination of lexical bias and altered auditory feedback was used to investigate the influence of higher-order linguistic knowledge on the perceptual aspects of speech motor control. Subjects produced monosyllabic real words or pseudo-words containing the vowel [ε] (as in "head") under conditions of altered auditory feedback involving a decrease in vowel first formant (F1) frequency. This manipulation had the effect of making the vowel sound more similar to [I] (as in "hid"), affecting the lexical status of produced words in two Lexical-Change (LC) groups (either changing them from real words to pseudo-words: e.g., less-liss, or pseudo-words to real words: e.g., kess-kiss). Two Non-Lexical-Change (NLC) control groups underwent the same auditory feedback manipulation during the production of [ε] real- or pseudo-words, only without any resulting change in lexical status (real words to real words: e.g., mess-miss, or pseudo-words to pseudo-words: e.g., ness-niss). The results from the LC groups indicate that auditory-feedback-based speech motor learning is sensitive to the lexical status of the stimuli being produced, in that speakers tend to keep their acoustic speech outcomes within the auditory-perceptual space corresponding to the task-related side of the word/non-word boundary (real words or pseudo-words). For the NLC groups, however, no such effect of lexical status is observed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".