Tracking the pseudo-pitch of unvoiced sounds: a hand-free interface modality for disabled users
Bibliographic record
Abstract
We developed a prototype of interface for persons with severe motor disabilities based on a new entry modality, namely unvoiced sounds like hissing, inspiration or expiration. Unlike sip-and-puff sensors, this modality uses the height of the sound as an analog parameter. Unvoiced sounds have no fundamental frequency (pitch). However they present a formant (pseudo-pitch), i.e., a peak of energy (typically above 800 Hz) that is perceived as the height of the sound. The pseudo-pitch can be partially controlled even in case of speech impairment. In our prototype, the pseudo-pitch is tracked in real time. Commands are entered by stabilizing the pseudo-pitch at the desired frequency. A voice-detection algorithm shuts off the entry during speech and strong noises, e.g., cough. It is possible to enter commands at a low volume and to speak aloud in the same microphone. Preliminary tests indicate that with the help of visual feedback, it is possible to produce 4 different commands and attain throughput above that throughputs above 166 bits/minute can be attained
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".