Acoustic analysis of the speech of patients with oral cancer: A methodological investigation comparing speech stimuli derived from different clinical outcome measures
Bibliographic record
Abstract
Background: Oral cavity cancer and its treatment reduce the quality of speech. Clinicians often utilize a variety of outcomes measures to assess speech function of patients with oral cavity cancer reducing the comparability of formant results due to differences in linguistics and phonetic contexts. Objective: To evaluate the degree of agreement in vowel space size in a F1-F2 plane, when comparing speech stimuli selected from a controlled environment (i.e., /hVd/ context) to speech stimuli segmented from two clinically available speech outcome measures in patients treated for cancer of the oral tongue. Methods: Voice recordings of nine patients treated with primary surgery for cancer of the oral cavity who attended functional assessment appointments (pre-operatively, and at 1-, 6-, and 12-months post-operatively) were analyzed. Agreement between vowel space size obtained from /hVd/ phrases and other speech assessments were compared using linear correlations and t-tests. Results: Vowel space size derived from /hVd/ phrases correlates strongly with corresponding estimates from other speech tasks (r = 0.72 to 0.82, p <0.0001). The other tasks had significantly reduced vowel space sizes compared to /hVd/ (t = 4.7 to 5, p<0.0001). Conclusion: Vowel space size estimates based on different speech tasks are mutually comparable and may offer insight to oral cancer speech production acoustics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".