Datasets:
license: other
task_categories:
- audio-classification
- question-answering
- text-generation
language:
- en
- ko
pretty_name: VocalCoachBench
size_categories:
- 10K<n<100K
tags:
- music
- singing
- vocal-coaching
- arxiv:2609.04241
configs:
- config_name: recordings
data_files:
- split: train
path: annotations/recordings.jsonl
- config_name: feedback_blocks
data_files:
- split: train
path: annotations/feedback_blocks.jsonl
- config_name: atomic_claims
data_files:
- split: train
path: annotations/atomic_claims.jsonl
- config_name: top3_issue_annotations
data_files:
- split: train
path: annotations/top3_issue_annotations.jsonl
- config_name: triplet_rankings
data_files:
- split: train
path: annotations/triplet_rankings.jsonl
- config_name: triplet_ranking_eval_units
data_files:
- split: train
path: annotations/triplet_ranking_eval_units.jsonl
- config_name: segment_annotations
data_files:
- split: train
path: annotations/segment_annotations.jsonl
- config_name: segment_consensus_events
data_files:
- split: train
path: annotations/segment_consensus_events.jsonl
- config_name: source_datasets
data_files:
- split: train
path: annotations/source_datasets.jsonl
VocalCoachBench
Accepted to NeurIPS 2026, Evaluations & Datasets Track
Hayeon Bang, Hounsu Kim, Wonil Kim, and Juhan Nam
Paper · Demo and leaderboard · Evaluation files
VocalCoachBench is a singing-audio benchmark for evaluating vocal coaching judgments. This release contains expert annotations for 515 singing recordings: free-form coaching feedback, atomic diagnosis/correction claims, Top-3 issue labels, same-song triplet rankings, and segment-conditioned issue labels.
Release version:
canonical515_physical_audio_1064refs. Canonical Top-3 denominator: 515 recordings (A=207, B=308).top3_issue_annotations.jsonlcontains 1,064 annotations covering all 515 recording IDs. An earlier filename-only join covered 511 IDs because four pairs of distinct physical audio files shared a submission filename. That pre-repair 511-ID count must not be used as the benchmark denominator. Seemetadata/CANONICAL_EVALUATION.mdandmetadata/top3_join_policy.json.
This release contains 1,064 recording-level expert reviews from 18 vocal trainers: 504 recordings have two experts, nine have six, and two have one. Its 4,506 feedback blocks yield 12,216 atomic claims: 6,162 diagnoses, 4,593 corrections, and 1,461 strengths. Earlier arXiv and dataset snapshots contain counts from before the physical-audio join repairs; the versioned counts and release notes govern this release.
Subsets:
same_song/ Dataset A: 207 Amazing Grace performances from DAMP-S-AG. Audio is not redistributed; useaudio_filenameto match the official release.diverse_song/ Dataset B: 308 recordings from multiple public singing datasets. Redistributable audio is included when source terms allow it.
What Is Included
| File | Rows | Description |
|---|---|---|
annotations/recordings.jsonl |
515 | One row per benchmark recording, with subset/source metadata and audio access fields. |
annotations/feedback_blocks.jsonl |
4,506 | Expert coaching feedback blocks, grouped by recording and anonymized annotator; covers all 515 recordings. |
annotations/atomic_claims.jsonl |
12,216 | Atomic issue, correction, and strength claims extracted from feedback blocks; covers all 515 recordings. |
annotations/top3_issue_annotations.jsonl |
1,064 | Expert Top-3 issue annotations joined by physical-audio identity; covers all 515 recordings. |
annotations/triplet_rankings.jsonl |
450 | Raw same-song triplet ranking annotations, with benchmark inclusion fields. |
annotations/triplet_ranking_eval_units.jsonl |
219 | One row per unique triplet, including the 2-of-3 pairwise agreement filter. |
annotations/segment_annotations.jsonl |
2,526 | Processed local segment feedback annotations over 304 diverse-song recordings; see the version limitation below. |
annotations/segment_consensus_events.jsonl |
262 | Segment-conditioned consensus events with IoU >= 0.3 and at least one shared issue tag. |
annotations/source_datasets.jsonl |
10 | Source dataset counts, links, licenses, and redistribution status. |
metadata/category_ontology.json |
- | Seven issue labels and their parent categories. |
metadata/triplet_ranking_policy.json |
- | Machine-readable triplet ranking inclusion policy and counts. |
metadata/top3_join_policy.json |
- | Machine-readable canonical Top-3 join policy, counts, source hashes, and fallback audit. |
metadata/claims_join_policy.json |
- | Physical-audio join policy, counts, and source hashes for feedback blocks and atomic claims. |
metadata/canonical_top3_recording_inventory.jsonl |
515 | One-row-per-recording Top-3 coverage audit with annotation counts and human-pair eligibility. |
metadata/CANONICAL_EVALUATION.md |
- | Frozen canonical Top-3 denominator and evaluation rules. |
metadata/PUBLIC_RELEASE.md |
- | Release version, final leaderboard definitions, and segment limitations. |
metadata/excluded_submission_files.json |
- | Historical/non-Top-3 exclusion metadata; superseded for canonical Top-3 by the hash-aware join policy. |
metadata/release_stats.json |
- | Release-level counts. |
metadata/croissant_rai_vocalcoachbench.json |
- | Machine-readable schema, source provenance, and Responsible AI metadata. |
evaluation/leaderboard.json |
- | Versioned final leaderboard with metric definitions, coverage, and provenance. |
evaluation/README.md |
- | Result definitions, evaluation policies, prompt snapshots, and reproducibility scope. |
Audio, when redistributed, is stored in audio/diverse_song/ and
audio/segment_clips_iou03/. Rows without redistributed audio have audio_path
or clip_path set to null.
Dataset Browser
A lightweight static browser is included at demo/index.html
for inspecting recordings, redistributed audio, expert feedback blocks, atomic
claims, Top-3 issue annotations, consensus segment events, and triplet ranking
metadata.
Source Datasets
VocalCoachBench uses existing public singing datasets as audio sources. The benchmark contribution is the vocal-coaching annotation layer, task definitions, evaluation metadata, and code for using these public sources. We do not claim the original public audio datasets as part of our submission.
| Source dataset | Records | Audio in this package | License / terms note | Official source |
|---|---|---|---|---|
| DAMP-S-AG | 207 | Not included; use official source | Smule Research Data License Agreement | link |
| PopBuTFy | 85 | Not included; permission pending | CC BY-NC-SA 4.0; author registration terms request that download links not be redistributed | link |
| N20EMv2 | 65 | Included | CC BY-SA 4.0 | link |
| LM-SSD | 7 | Included | CC BY 4.0 | link |
| NUS-48E | 41 | Included | CC BY 4.0 | link |
| MedleyDB | 32 | Not included; permission pending | CC BY-NC-SA 4.0 with author request not to republish without consent | link |
| MedleyVox | 12 | Included | CC BY-NC-SA 4.0 | link |
| MRSSing | 43 | Included | CC BY 4.0 | link |
| URSing | 14 | Included | CC BY 4.0 | link |
| GTSinger | 9 | Included | CC BY-NC-SA 4.0 | link |
Schema Notes
The public join key is recording_id. For construction of the canonical
Dataset-B Top-3, feedback-block, and atomic-claim tables, raw submissions are first resolved to physical recordings
by audio SHA-256 and only then assigned recording_id; joining raw annotations
by audio_filename alone is prohibited because filenames are not unique. Most
rows also include dataset and subset; annotator IDs are stable anonymized
IDs. Feedback blocks and atomic claims can also be joined by block_uid.
The final evaluation prompts use these seven issue labels:
PITCHRHYTHMDICTIONBREATHPHONATIONTECHNIQUEEXPRESSION
Parent categories are Musical Accuracy, Technical Production, and Delivery.
The released annotation files and metadata/category_ontology.json retain the
legacy label VOCALIZATION. It is an alias of PHONATION, not an eighth class;
normalize the two labels to the same class when scoring. See
metadata/category_ontology.json for the parent mapping.
Triplet ranking evaluation uses only triplets with at least 2-of-3 pairwise
agreement between two expert rankings. Use
triplet_ranking_eval_units.jsonl or filter triplet_rankings.jsonl with
benchmark_included == true. This yields 378
reference annotations over 189 unique evaluation
triplets.
Evaluation and Version Notes
The final leaderboard, updated 2026-10-26, uses
schema vcb_final_leaderboard_v1 and dataset version
canonical515_physical_audio_1064refs. Its policy is strict_all_attempts:
stored first responses are evaluated, and malformed or missing outputs count as
errors. Expert references have equal total weight per recording.
| Evaluation | Main denominator and interpretation |
|---|---|
| Top-3 | Seven-class macro-F1 over 515 recordings / 1,064 expert references; each recording has unit total weight. |
| Segment | Seven-class macro-F1 over the frozen 262 consensus events. |
| Direct and score-derived ranking | 189 triplets / 567 pair decisions, scored against both expert orders: 1,134 reference attempts. These are separate tasks. |
| Diagnosis strict hit / hit | 6,162 expert issue claims; strict hit counts STRICT_HIT, and hit also includes COARSE_HIT. |
| Prescription validity / diagnosis-to-prescription E2E | 2,575 fixed slots (515 × 5); missing prescriptions count as failures. |
| Human expert-vs-expert Top-3 | 513 recordings with at least two experts; the two single-expert recordings are excluded. |
The final leaderboard's Claims extension reports format failures: invalid JSON
produces zero emitted claims and remains in the fixed denominators. Main and
Simple prompt protocols and concatenated-audio Direct variants are labeled
separately. Unavailable results are null, not zero. See
evaluation/README.md for the full metric definitions.
Segment limitation: the released 2,526 segment annotations cover 304 Dataset-B recordings, and the leaderboard retains its frozen 262-event set. A separately staged physical-audio join repair produces 2,583 annotations over 308 recordings and 271 consensus events. That staged revision is not installed in this release; it needs new audio clips and model predictions before a new benchmark version can replace the 262-event results. See metadata/PUBLIC_RELEASE.md.
Audio Redistribution
- DAMP-S-AG same-song audio is excluded. Download it from the official Zenodo
release and match by
audio_filename. - PopBuTFy and MedleyDB audio are excluded pending redistribution permission.
- Other diverse-song audio is included when allowed by source terms.
Redistributed full-recording audio files are copied from their public source datasets without additional audio processing. The segment clips are derived time crops for the segment-conditioned task. We do not claim copyright or ownership over the original source audio; users should follow and cite the original source datasets and their licenses or terms.
If any original dataset author or maintainer requests removal of redistributed audio, or prefers source-link-only access, we will remove the affected audio files from this package and switch those rows to official-source-link based distribution.
Privacy
Annotator names, raw local paths, and source submission filenames containing annotator names are not included in public annotation rows.
Loading Example
from datasets import load_dataset
repo_id = "Hayeonbang/VocalCoachBench"
recordings = load_dataset(repo_id, "recordings", split="train")
claims = load_dataset(repo_id, "atomic_claims", split="train")
triplet_units = load_dataset(repo_id, "triplet_ranking_eval_units", split="train")
same_song = recordings.filter(lambda row: row["subset"] == "same_song")
eval_triplets = triplet_units.filter(lambda row: row["benchmark_included"])
The train split name is a storage convention for the annotation tables, not a
benchmark training partition. Record the dataset revision when reporting
results, and pass revision="<commit-sha>" to reproduce that snapshot.
Citation
If you use VocalCoachBench, please cite the paper and the original audio datasets relevant to your work:
@misc{bang2026vocalcoachbench,
title = {VocalCoachBench: Benchmarking Audio-Language Models on Expert Feedback for Singing},
author = {Hayeon Bang and Hounsu Kim and Wonil Kim and Juhan Nam},
year = {2026},
eprint = {2609.04241},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.04241},
note = {Accepted to the NeurIPS 2026 Evaluations \& Datasets Track}
}