TruVox Web-Based Software for Vocal Pitch Training in Transgender Women: Development and Single-Session Evaluations
Bibliographic record
Abstract
BACKGROUND: Transgender people often experience distress due to a mismatch between their gender and the way their voice is perceived (eg, transgender women with low pitch), which significantly reduces their mental health and quality of life. This is especially a problem for transfeminine people and can be reduced with gender-affirming voice training (GAVT), but such training is often inaccessible due to factors such as price and geographical constraints. OBJECTIVE: We aim to improve the limited availability of GAVT by developing and testing a free web-based software platform (named TruVox; University of Cincinnati) that would combine real-time feedback about the user's voice with structured vocal pitch exercises for transfeminine people. METHODS: The current publicly accessible TruVox prototype focuses on vocal pitch training with 5 structured exercises that provide real-time pitch visualizations as well as supporting videos and text. It was tested in 2 evaluation stages: initial remote usability evaluations and a later single-session in-person evaluation with 21 transfeminine participants under the supervision of 2 researchers. In remote evaluations, participants reported bugs and usability issues that were iteratively addressed. In the in-person evaluation, participants tested the final software prototype and filled out the System Usability Scale, then performed 10 repetitions of different exercises to gauge performance improvement with practice. They also filled out the Intrinsic Motivation Inventory for each exercise. RESULTS: The System Usability Scale score had a mean of 79.8 (SD 12.8) on a 100-point scale, Intrinsic Motivation Inventory scores were high (eg, interest/enjoyment over 11/14), and exercise performance significantly improved in all but 1 exercise (P values ranging from below .001 to .095). As qualitative feedback, participants requested to be able to use the software without much preparation and suggested several desirable future features, such as performance tracking and goal-setting. CONCLUSIONS: While the pitch training module should not be considered a complete GAVT package, TruVox represents a promising foundation for further GAVT software because it was perceived as usable and motivating and allowed participants to improve their exercise performance. To our knowledge, TruVox is the first GAVT software that combines real-time voice visualization with structured exercises, and this study represents the first quantitative human subjects evaluation of GAVT software. In the future, TruVox will be expanded with additional modules such as resonance training, then tested in longer-term trials.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".