Paper year
2020
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
2020
Citations
8
Authors
1
Topic labels
3
Source readout
Transactions of the International Society for Music Information Retrieval
tismir
Core corpus
6
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
0
Top 50
0
Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
Emerging
No materialized row for this family in the resolved run
This paper did not surface into the current materialized family row set.
Bridge
No materialized row for this family in the resolved run
This paper did not surface into the current materialized family row set.
Under-cited
No materialized row for this family in the resolved run
This paper did not surface into the current materialized family row set.
This paper is about the story of my relationship, as a contemporary music composer, with computational tools that are situated in the areas of signal processing, machine learning and music information retrieval (MIR). I believe that sharing this story can be useful to the MIR community since it illustrates the problems that can arise when you try to use these techniques in the context of contemporary music creation. Since this is a personal story, I will refer to experiences that I had during about fifteen years of usage of MIR-related technologies. I will show how these technologies tried to (unsuccessfully) shape my musical thinking and why I believe that some of them have come to an end. Finally, I will propose new possible directions for the future of MIR.
Neighborhood labels
Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Music and Audio ProcessingMusic Technology and Sound StudiesDiverse Musicological Studies
Neighbor surface
Similar papers use a separately configured neighbor embedding; it may differ from the embedding version used by the current ranked run.
A Case for Reproducibility in MIR: Replication of 'A Highly Robust Audio Fingerprinting System'
0.625Next 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.