Interaction of Speech Coders and Atypical Speech I
Bibliographic record
Abstract
We investigated how standard speech coders, currently used in modern communication systems, affect the intelligibility of the speech of persons who have common speech and voice disorders. Three standardized speech coders (viz., GSM 6.10 [RPE-LTP], FS1016 [CELP], FS1015 [LPC]) and two speech coders based on subband processing were evaluated for their performance. Coder effects were assessed by measuring the intelligibility of vowels and consonants both before and after processing by the speech coders. Native English talkers who had normal hearing identified these speech sounds. Results confirmed that (a) all coders reduce the intelligibility of spoken language; (b) these effects occur in a consistent manner, with the GSM and CELP coders providing the least degradation relative to the original unprocessed speech; and (c) coders interact with individual voices so that speech is degraded differentially for different talkers.
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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 | 0.013 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".