Paper dossier

ChoraleBricks: A Modular Multitrack Dataset for Wind Music Research

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Paper year

2025

Citations

3

Authors

2

Topic labels

3

Source readout

Source and corpus status

Venue

Transactions of the International Society for Music Information Retrieval

Source slug

tismir

Corpus placement

Core corpus

Similarity rows

6

Ranking readout

Where this paper lands in the current run

Run shadow-generalization-product-candidate-ranking-v1Top 50 surfaced

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

3

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 7

0.515

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=0.8318, citation_velocity=0.1800, topic_growth=0.8636, diversity_penalty=0.0000

Why this surfaced | 3 used | 1 penalty | 1 not computed
Embedding slice fit (corpus centroid)used

Embedding slice fit (corpus centroid): high; used in final ranking (contribution to score: 0.1664)

Recent attentionused

Recent attention: low; used in final ranking (contribution to score: 0.0900)

Topic momentumused

Topic momentum: high; used in final ranking (contribution to score: 0.2591)

Cross-cluster signalnot computed

Cross-cluster signal: not computed for this run

Similarity penaltypenalty

Similarity penalty: reduces score when non-zero (contribution to score: 0.0000)

Bridge

In top 50 at rank 6

0.624

Multi-topic paper in active topics; no cluster_version on this run so bridge_score was not computed.

Signals: citation_velocity=0.1800, topic_growth=0.8636, diversity_penalty=0.0000

Why this surfaced | 2 used | 1 penalty | 2 not computed
Semantic matchnot computed

Semantic match: not computed for this run

Recent attentionused

Recent attention: low; used in final ranking (contribution to score: 0.0630)

Topic momentumused

Topic momentum: high; used in final ranking (contribution to score: 0.5613)

Cross-cluster signalnot computed

Cross-cluster signal: not computed for this run

Topic breadth penaltypenalty

Topic breadth penalty: reduces score when non-zero (contribution to score: 0.0000)

Under-cited

In top 50 at rank 43

0.519

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=0.1800, topic_growth=0.8636, diversity_penalty=0.5579

Why this surfaced | 2 used | 1 penalty | 2 not computed
Semantic matchnot computed

Semantic match: not computed for this run

Recent attentionused

Recent attention: low; used in final ranking (contribution to score: 0.0540)

Topic momentumused

Topic momentum: high; used in final ranking (contribution to score: 0.6045)

Cross-cluster signalnot computed

Cross-cluster signal: not computed for this run

Pool popularity penaltypenalty

Pool popularity penalty: reduces score when non-zero (contribution to score: -0.1395)

Abstract

Concert band and wind music are deeply embedded in society and play a significant role in the cultural landscape of many countries, including Germany and Austria, particularly within the amateur music scene. However, this type of music, as well as research on wind and brass instruments in general, remains largely overlooked in the field of music information retrieval (MIR). In this paper, we address this underexplored area by introducing ChoraleBricks, a framework featuring multitrack recordings of ten different chorales, each comprising four musical parts: soprano, alto, tenor, and bass. At its core, ChoraleBricks provides isolated recordings of individual parts performed by a diverse selection of wind instruments, including flute, oboe, clarinet, trumpet, saxophone, baritone horn, trombone, and tuba. These isolated recordings act as building blocks or "bricks" that can be modularly superimposed to create full mixes with varying instrumentation. In addition, ChoraleBricks provides sheet music, time‑aligned symbolic music representations, conducting videos, and reference annotations such as fundamental frequencies and note events. The framework is further enhanced by Python software tools that support parsing, mixing, annotation, and modular combination of the recorded audio material. With all multimedia and software components available as open‑source, ChoraleBricks provides a versatile framework for generating and augmenting datasets for polyphonic wind music. It supports systematic experimentation and facilitates evaluation across various research topics, including multi‑pitch estimation, note transcription, audio alignment, and music education applications.

Authors

  • Stefan Balke
  • Meinard Müeller

Neighborhood labels

Topics

3 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 StudiesAnimal Vocal Communication and Behavior

Neighbor surface

Similar papers

6 total neighborsEmbedding v1-title-abstract-1536-cleantext-r3

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