Designing Speech and Multimodal Interactions for Mobile, Wearable, and Pervasive Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Traditional interfaces are continuously being replaced by mobile, wearable, or pervasive interfaces. Yet when it comes to the input and output modalities enabling our interactions, we have yet to fully embrace some of the most natural forms of communication and information processing that humans possess: speech, language, gestures, thoughts. Very little HCI attention has been dedicated to designing and developing spoken language and multimodal interaction techniques, especially for mobile and wearable devices. In addition to the enormous, recent engineering progress in processing such modalities, there is now sufficient evidence that many real-life applications do not require 100% accuracy of processing multimodal input to be useful, particularly if such modalities complement each other. This multidisciplinary, two-day workshop will bring together interaction designers, usability researchers, and general HCI practitioners to analyze the opportunities and directions to take in designing more natural interactions with mobile and wearable devices, and to look at how we can leverage recent advances in speech and multimodal processing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it