What’s The Talk on VUI Guidelines? A Meta-Analysis of Guidelines for Voice User Interface Design
Bibliographic record
Abstract
Over the past decade, voice user interface (VUI) design has been steadily growing, along with a growing VUI presence in consumer markets. However, there is currently a lack of widely-established guidelines for VUI design. While many sets of VUI guidelines have been proposed, they tend to be developed independently of each other, leading to a lack of consensus on appropriate guidelines for VUI design. This can hinder the wider adoption of practical VUI guidelines. To address this gap, we performed a large-scale meta-analysis of 336 VUI design guidelines that have been proposed in academic literature. Using thematic analysis, we present a unified and synthesized set of 14 guidelines, representing the most universally proposed principles of VUI design as captured by the 336 VUI guidelines identified in academic literature. We hope that this synthesized set can address several of the challenges to the adoption of VUI guidelines in design practice.
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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 | 0.195 | 0.469 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.027 | 0.022 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".