On the prediction of speech quality ratings of tracheoesophageal speech using an auditory model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Total laryngectomy is often the treatment of choice for many patients suffering from laryngeal cancer. This procedure alters the speech production mechanism, and tracheoesophageal (TE) speech is an alternative where the pulmonary air is forced through the esophagus. TE speech is often characterized by poor intelligibility and voice quality. Acoustic analysis of TE speech has the potential of quantifying the voice quality and assisting the speech pathologist in determining and monitoring the therapy process. In this paper, we apply two different methods for predicting the voice quality ratings of TE speakers by naive listeners: (a) conventional spectral and linear prediction measurements that were investigated in earlier studies, and (b) a methodology based on a perceptual auditory model that attempts to mimic the speech quality perception by a normal hearing listener. Experimental results with a database of 35 TE speakers showed that the auditory-model based approach significantly outperforms the traditional methods.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it