Sonic Enhancements to Museum Exhibitions: Strategies, Challenges, and Opportunities
Bibliographic record
Abstract
Museums are increasingly offering exhibition elements, often mediated through digital technology and in non-visual modalities, to engage visitors beyond artifacts and text panels. This thesis project focuses on the addition of sound or music to complement exhibitions on other topics. These sonic enhancements, including recorded music and soundscapes, visitor-initiated sound effects, and more, represent a move towards layered and multisensory exhibition design in museums. My thesis uses case studies and interviews to address how, why, and to what effect sounds have been added to museum exhibitions historically and currently, as well as how to add them more effectively going forward. My paper first presents a literature review, including a short history of sonic enhancements to museum exhibitions. I then present eight case studies of sonic enhancements across five Ontario museums of different sizes and types. I conducted semi- structured interviews with seven museum professionals about their experiences and intentions in developing these sonic exhibition elements. Ultimately, I find that sound is being used as an important but not-crucial addition to exhibitions. Sound is often used interpretively: to fit a message, evoke another time or place, or prompt new perspectives on artifacts. Secondary outcomes include the creation of atmosphere and opportunities for visitor participation. Other findings involve the importance of authentic sounds, the use of terms such as “immersive,” “interactive,” and “multisensory” in museum practice, and careful planning versus ad hoc experimentation in developing sonic elements. While some priorities appeared across case studies (e.g., the importance of interpretive fit), others divided interviewees and depended on context (e.g., sound bleed between exhibition sections). There were noted process challenges, especially technology and copyright limitations and the risk of sounds causing confusion. Overall, however, interviewees reported that visitors enjoy and benefit from sonic exhibition elements. My paper concludes with some suggestions for best practices for enhancing exhibitions with sound effectively and accessibly.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".