Paper year
2024
Detect emerging, bridge-candidate, and undercited papers inside a curated audio-ML corpus, then expose the signals behind every recommendation.
Paper dossier
Review source metadata, abstract, authors, topics, and local similarity context before moving into explanation and ranking views.
Paper year
2024
Citations
11
Authors
4
Topic labels
3
Source readout
Journal of the Audio Engineering Society
jaes
Core corpus
Not available yet
Ranking readout
This block uses the same resolved ranking run as Recommended. Ranks here are materialized paper_scores ranks; live Emerging may be reordered by the bounded ML scorer. Family rank is global within each family, but rank is only shown when this paper lands inside the surfaced top 50.
Families present
3
Top 50
1
Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
Emerging
In top 50 at rank 8
Emerging: embedding slice fit vs included-corpus centroid (title+abstract), plus citation velocity and topic growth; not universal relevance. Bridge signal not used here.
Signals: semantic=0.8199, citation_velocity=0.4400, topic_growth=0.4333, diversity_penalty=0.0000
Embedding slice fit (corpus centroid): high; used in final ranking (contribution to score: 0.1640)
Recent attention: medium; used in final ranking (contribution to score: 0.2200)
Topic momentum: medium; used in final ranking (contribution to score: 0.1300)
Cross-cluster signal: not computed for this run
Similarity penalty: reduces score when non-zero (contribution to score: 0.0000)
Bridge
Present in run, outside top 50
Multi-topic paper in active topics; no cluster_version on this run so bridge_score was not computed.
Signals: citation_velocity=0.4400, topic_growth=0.4333, diversity_penalty=0.0000
Semantic match: not computed for this run
Recent attention: medium; used in final ranking (contribution to score: 0.1540)
Topic momentum: medium; used in final ranking (contribution to score: 0.2817)
Cross-cluster signal: not computed for this run
Topic breadth penalty: reduces score when non-zero (contribution to score: 0.0000)
Under-cited
Present in run, outside top 50
Low-cite candidate pool (see docs/candidate-pool-low-cite.md v0): core corpus, recency floor, citation ceiling, title+abstract gate; popularity penalty among pool members only. Semantic and bridge not yet modeled.
Signals: citation_velocity=0.4400, topic_growth=0.4333, diversity_penalty=1.0000
Semantic match: not computed for this run
Recent attention: medium; used in final ranking (contribution to score: 0.1320)
Topic momentum: medium; used in final ranking (contribution to score: 0.3033)
Cross-cluster signal: not computed for this run
Pool popularity penalty: reduces score when non-zero (contribution to score: -0.2500)
Experiments testing sound for augmented reality can involve real and virtual sound sources. Paradigms are either based on rating various acoustic attributes or testing whether a virtual sound source is believed to be real (i.e., evokes an auditory illusion). This study compares four experimental designs indicating such illusions. The first is an ABX task suitable for evaluation under the authenticity paradigm. The second is a Yes/No task, as proposed to evaluate plausibility. The third is a three-alternative-forced-choice (3AFC) task using different source signals for real and virtual, proposed to evaluate transfer-plausibility. Finally, a 2AFC task was tested. The renderings compared in the tests encompassed mismatches between real and virtual room acoustics. Results confirm that authenticity is hard to achieve under nonideal conditions, and ceiling effects occur because differences are always detected. Thus, the other paradigms are better suited for evaluating practical augmented reality audio systems. Detection analysis further shows that the 3AFC transfer-plausibility test is more sensitive than the 2AFC task. Moreover, participants are more sensitive to differences between real and virtual sources in the Yes/No task than theory predicts. This contribution aims to aid in selecting experimental paradigms in future experiments regarding perceptual and technical requirements for sound in augmented reality.
Neighborhood labels
Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Hearing Loss and RehabilitationTactile and Sensory InteractionsImage and Video Quality Assessment
Neighbor surface
Similar papers use a separately configured neighbor embedding; it may differ from the embedding version used by the current ranked run.
No embedding-backed neighbors available for this paper/version yet.
Next handoff
01
Use Recommended to see whether this paper behaves like an emerging or undercited signal in the current ranked feed, or how it appears on the bridge preview / diagnostics view.
02
Use Trends to understand whether its attached labels are heating up or cooling down inside the curated corpus.
03
Use Evaluation to compare the dossier readout against citation and recency baselines for the same resolved family run.