Intelligibility before and after advanced head and neck cancer with concomitant chemoradiotherapy
Bibliographic record
Abstract
Evaluations of speech intelligibility based on a read passage are often used in the clinical situation to assess the impact of the disease and/or treatment on spoken communication.Although scale-based measures are often used in the clinical setting, these measures are susceptible to listener response bias.Automatic evaluation tools are being developed in response to some of the drawbacks of perceptual evaluation, however, large corpora judged by listeners are needed to improve and test these tools.To this end, the NKI-CCRT corpus with individual listener judgements on the intelligibility of recordings of 55 speakers treated for cancer of the head and neck will be made available for restricted scientific use.The corpus contains recordings and perceptual evaluations of speech intelligibility over three evaluation moments: before treatment and after treatment (10-weeks and 12-months).Treatment was by means of chemoradiotherapy (CCRT).Thirteen recently graduated speech pathologists rated the speech intelligibility of the recordings on a 7-point scale.Information on recording and perceptual evaluation procedures is presented in addition to preliminary rater reliability and agreement information.Preliminary results show that for many speakers speech intelligibility is rated low before cancer treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".