Acoustic Measures of Dysphonia in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
PURPOSE: Identifying efficacious measures to characterize dysphonia in complex neurodegenerative diseases is key to optimal assessment and intervention. This study evaluates the validity and sensitivity of acoustic features of phonatory disruption in amyotrophic lateral sclerosis (ALS). METHOD: Forty-nine individuals with ALS (40-79 years old) were audio-recorded while producing a sustained vowel and continuous speech. Perturbation/noise-based (jitter, shimmer, and harmonics-to-noise ratio) and cepstral/spectral (cepstral peak prominence, low-high spectral ratio, and related features) acoustic measures were extracted. The criterion validity of each measure was assessed using correlations with perceptual voice ratings provided by three speech-language pathologists. Diagnostic accuracy of the acoustic features was evaluated using area-under-the-curve analysis. RESULTS: Perturbation/noise-based and cepstral/spectral features extracted from /a/ were significantly correlated with listener ratings of roughness, breathiness, strain, and overall dysphonia. Fewer and smaller correlations between cepstral/spectral measures and perceptual ratings were observed for the continuous speech task, although post hoc analyses revealed stronger correlations in speakers with less perceptually impaired speech. Area-under-the-curve analyses revealed that multiple acoustic features, particularly from the sustained vowel task, adequately differentiated between individuals with ALS with and without perceptually dysphonic voices. CONCLUSIONS: Our findings support using both perturbation/noise-based and cepstral/spectral measures of sustained /a/ to assess phonatory quality in ALS. Results from the continuous speech task suggest that multisubsystem involvement impacts cepstral/spectral analyses in complex motor speech disorders such as ALS. Further investigation of the validity and sensitivity of cepstral/spectral measures during continuous speech in ALS is warranted.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".