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Access to the YTSV token releases is granted for non-commercial research use. These tokens are derived from YouTube score-following videos whose underlying media remains the property of its respective uploaders; only discrete token representations are distributed here. The YTSV metadata this derives from is licensed CC BY-NC-SA 4.0, so the non-commercial and share-alike terms travel to these tokens and to anything derived from them. Requests are reviewed manually; please describe your intended use so it can be assessed.
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YTSV performance-audio tokens (U-MusT, unidac4)
DAC audio tokens for the YouTube Score Video (YTSV) dataset, the main dataset contribution of U-MusT — 433,920 image–audio pairs from 12,217 score-following videos, 1,341 hours in total, covering roughly 10,000 pieces by more than 2,000 composers. An order of magnitude larger than any prior music modal-translation corpus.
Tokenized with unidac4-ytsv, a 4-codebook DAC. Roughly 31 GB across 446k token files before sharding.
No video or audio is redistributed. These are tokens only. The video metadata and the preprocessing pipeline that produced them live in MALerLab/youtube-score-video-dataset; the media itself must be downloaded from YouTube by you.
Layout
The token tree is sharded into one gzipped tar per collection group, because the uncompressed form runs to over a million small files — impractical for a Hub repository to serve.
audio/0-2.tar.gz
audio/0-3.tar.gz
... 18 shards, ~1.7 GB each
Each archive expands to <group>/segments/<youtube_id>/audio_tokens/..., so extracting all
shards under one directory reconstructs the layout the U-MusT loaders expect:
hf download malerlab/ytsv-unidac4-ytsv --repo-type dataset --local-dir shards/
mkdir -p dataset/latent_score_dataset_tokens
for f in shards/audio/*.tar.gz; do
tar -xzf "$f" -C dataset/latent_score_dataset_tokens
done
Split manifests for the training, validation and test partitions are in the
code repository under dataset_pair_paths/
(lsyt.json.gz for all instrumentation, lsyt_piano.json.gz for the piano subset).
Token files contain shift variants, not a single tokenization
Read this before loading anything. A one-sample offset in audio changes the discrete token assignment almost entirely, so training on a single tokenization makes a model brittle to offsets it will certainly meet at inference. Every file here instead stores a stack of discretization-shift variants.
YTSV audio tokens are .dac (Descript Audio Codec) files whose codes array has shape
(9, 4, T):
| Axis | Size | Meaning |
|---|---|---|
| 0 | 9 | temporal shift variants — sample offsets from −20 to +20 in steps of 5 |
| 1 | 4 | the DAC's four codebooks |
| 2 | T |
frames, at roughly 86 token sets per second |
Index 0 on the leading axis is the unshifted tokenization. Audio is 44.1 kHz mono. Directories
named mono_augmented carry the variant stack; the rare mono directories carry a single
tokenization.
Full details of the augmentation scheme are in Appendix B of the supplementary material, published with the article at doi.org/10.1109/TASLPRO.2025.3648794.
Licensing
Released under CC BY-NC-SA 4.0, matching the license of the YTSV metadata it derives from.
The underlying videos are the property of their respective uploaders and are not covered by this license. This repository distributes only discrete token representations computed from them. The full per-corpus license table for the project, and the conflicts between corpora, are documented in the code repository. This is not legal advice — satisfy yourself that your intended use is permitted.
Citation
@article{jung2026umust,
title = {U-MusT: A Unified Framework for Cross-Modal Translation of Score Images, Symbolic Music, and Performance Audio},
author = {Jung, Jongmin and Kim, Dongmin and Lee, Sihun and Cho, Seola and Soh, Hyungjoon and Bukey, Irmak and Donahue, Chris and Jeong, Dasaem},
journal = {IEEE Transactions on Audio, Speech and Language Processing},
volume = {34},
pages = {1876--1891},
year = {2026},
doi = {10.1109/TASLPRO.2025.3648794}
}
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