Ontology and rule based retrieval of sound objects in augmented audio reality system for museum visitors
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
ec(h)o is an "augmented reality interface" utilizing spatialized soundscapes and a semantic web approach to information. The initial prototype is designed for a natural history and science museum. The platform is designed to create a museum experience that consists of a physical installation and an interactive virtual layer of three-dimensional soundscapes that are physically mapped to the museum displays. The source for the audio data is digital sound objects. The digital objects originate in a network of object repositories that connect digital content from one museum with other museums collections. The interface enables people to interact with the system by movement and object manipulation-based gestures without the direct use of a computer device. The focus of this paper is the retrieval mechanism for the sound objects for the museum visitor. The retrieval mechanism is built on the user model and conceptual descriptions of the sound object and museum artifacts in the form of ontologies for sound and psychoacoustics, topic ontology and Conceptual Reference Model for museum information. The retrieval criteria are represented as inference rules that represent knowledge from psychoacoustics, cognitive domain and composition aspects of interaction. The system will be demonstrated in exhibition space in Nature Museum in Ottawa in January 2003.
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