Evaluations of /r/ attempts of children in speech therapy by speech-language pathologists and child educators
Bibliographic record
Abstract
Background: Previous studies of treatment for English /r/ (designated with the North American symbol /r/) have mainly used Speech-Language Pathologists (SLPs) as expert listeners and scalar rating methods (e.g. Chaney, 1998). Tasks have involved rank order judgment of natural or synthesized speech stimuli, with a variety of trained and untrained adult and child listeners. Aims: The present study set out to compare expert and untrained listener evaluations of different /r/ attempts by children. The two comparison groups were SLPs and Educators (teachers or child care workers). A secondary objective was to compare an identification listening task with a paired comparison task. Methods and Procedures: Sixteen /r/ syllables ([ræ], [ar]) were extracted from pre- and post-treatment field recordings of four Canadian English-speaking children. The two tasks (identification of tokens as /r/ or not /r/, and a forced choice comparison of /r/ pairs) were presented through Microsoft Powerpoint under headphones. Twenty SLPs and eighteen Educators judged the quality of the /r/ attempts. Formant analyses were also made of the stimuli. Outcomes and Results: The expert listeners (SLPs) showed higher intra-rater reliability: 91% on the pairwise comparison task and 81% on the identification task, compared with 84%. and 78% for the untrained listeners respectively. Inter-rater reliability on single measures (ICC Educators=.51 in comparison, .21 in identification; SLPs=.42 in comparison; .31 in identification) was lower than that of average measures (ICC Educators=.96 in comparison, .87 in identification; SLPs=.95 in comparison; .92 in identification) Rank order of sample ratings as on- or off-target was similar between the two groups. The rankings matched the normative formant data for /r/ published in Guenther et al. (1999) and Flipsen et al. (2000, 2001) for the best tokens, with SLPs providing a ranking closer to the acoustic norms. Conclusions and Implications: Trained listeners appeared to be better able to identify nuances in /r/ quality, as confirmed by acoustic analysis of /r/ tokens. Intra-rater reliability was higher for SLPs despite greater disagreement among SLPs for single measures of inter-rater reliability. The paired comparison task had higher reliability scores than the identification task for both listener groups
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".