Designing co-located multi-device audio experiences
Bibliographic record
Abstract
The widespread distribution and diversification of mobile computing devices presents new opportunities for the development and consumption of new interactive, immersive and accessible media experiences using multiple connected devices. Tools now exist for the creation of these experiences; however, there is still limited understanding of the best design practices and use cases for the technology, especially in the context of audio experiences. Furthermore, the little extant research on multi-device audio experiences is fragmented, leading to problems navigating the research. The work in this thesis approached these issues through a two step programme. The first step involved improving understanding of these experiences from a conceptual perspective and identifying relevant design concepts. The application space of co-located multi-device audio experiences is explored and documented through a review of the literature and a survey. Through qualitative analysis of the obtained information, an initial set of seven design dimensions, synchronisation, context, position, relationship, interactivity, organisation, and distribution, were proposed that capture distinct design considerations and can be used to characterise and compare experiences. The dimensions were evaluated in a series of workshops where they were found to be useful as a co-design tool for experience ideation. The second step comprised of identifying new experience opportunities and using distinct yet complementary methods to gain new insights. Two case studies were conducted that focused on delivering concurrent personal and shared audio on different devices. The first focused on the design and technical implementation of a novel multi-device audio prototype using a practice-based approach, where a new design dimension, perception, was also identified. The second focused on the evaluation of the listening experience of using wireless earbuds with active transparency for augmenting TV audio through a controlled listening test. A novel experimental method is presented and production recommendations were provided for this multi-device audio reproduction medium.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".