| --- |
| pretty_name: MSR Challenge 2025 Evaluation Set |
| license: cc-by-nc-4.0 |
| task_categories: |
| - audio-to-audio |
| language: |
| - zxx |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - music |
| - audio-restoration |
| - source-separation |
| --- |
| |
| # MSR Challenge 2025 Evaluation Set |
|
|
| This repository contains the held-out evaluation audio distributed for the inaugural Music Source Restoration (MSR) Challenge associated with ICASSP 2026. The task is to recover an unprocessed musical source from a professionally produced or otherwise degraded mixture. |
|
|
| The release has 1,496 stereo mixture clips across eight instrument classes. Reference targets are available for 1,128 examples; the remaining 368 examples are mixture-only because the organizer archive did not include references for the cylinder, live, or radio subsets. |
|
|
| ## Dataset structure |
|
|
| ```text |
| ./ |
| ├── metadata.jsonl |
| ├── mixtures/ |
| │ └── {instrument}/{file_id}.flac |
| └── targets/ |
| └── {instrument}/{file_id}.flac |
| ``` |
|
|
| All audio is stereo FLAC at 48 kHz and 10 seconds long. Mixtures and targets retain their original encoded bit depths. |
|
|
| | Subset | Mixtures | Targets | Description | |
| |---|---:|---:|---| |
| | `non-blind` | 1,000 | 1,000 | Organizer non-blind evaluation material | |
| | `streaming` | 128 | 128 | Lossy-codec conditions | |
| | `cylinder` | 112 | 0 | Historical cylinder recordings | |
| | `live` | 128 | 0 | Live/acoustic degradation condition | |
| | `radio` | 128 | 0 | Radio degradation condition | |
| | **Total** | **1,496** | **1,128** | | |
|
|
| Instrument counts are 189 each for Bass, Drums, Guitars, Keyboards, Orchestral Elements, Percussions, and Vocals, and 173 for Synthesizers. |
|
|
| ## Metadata fields |
|
|
| - `file_id`: stable identifier used by the organizer archives. |
| - `mixture_file_name`: relative path to the input audio. |
| - `target_file_name`: relative path to the reference audio, or `null` when unavailable. |
| - `has_target`: whether a reference is included. |
| - `subset`: `non-blind`, `streaming`, `cylinder`, `live`, or `radio`. |
| - `instrument`: target instrument class. |
| - `augmentation_type`, `augmentation_code`: codec/augmentation description when present. |
|
|
| ## Intended use |
|
|
| This dataset is intended for evaluation of music source restoration and related source-separation or audio-restoration systems. Do not treat the mixture-only examples as having negative or silent targets. Users should report results separately by subset and instrument where possible. |
|
|
| ## Citation |
|
|
| Please cite the challenge summary when using this evaluation set. The original MSR task paper and the related MSRBench paper are also included below. |
|
|
| ```bibtex |
| @inproceedings{zang2026msrchallenge, |
| title = {Summary of the Inaugural Music Source Restoration Challenge}, |
| author = {Zang, Yongyi and Hai, Jiarui and Ge, Wanying and Kong, Qiuqiang and Dai, Zheqi and Wang, Helin and Mitsufuji, Yuki and Plumbley, Mark D.}, |
| booktitle = {ICASSP 2026--2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| pages = {21853--21855}, |
| year = {2026}, |
| doi = {10.1109/ICASSP55912.2026.11462762} |
| } |
| |
| @inproceedings{zang2025music, |
| title = {Music Source Restoration}, |
| author = {Zang, Yongyi and Dai, Zheqi and Plumbley, Mark D. and Kong, Qiuqiang}, |
| booktitle = {2025 IEEE International Workshop on Multimedia Signal Processing (MMSP)}, |
| pages = {138--143}, |
| year = {2025}, |
| doi = {10.1109/MMSP64401.2025.11324269} |
| } |
| |
| @inproceedings{zang2026msrbench, |
| title = {MSRBench: A Benchmarking Dataset for Music Source Restoration}, |
| author = {Zang, Yongyi and Hai, Jiarui and Ge, Wanying and Dai, Zheqi and Wang, Helin and Mitsufuji, Yuki and Kong, Qiuqiang and Plumbley, Mark D.}, |
| booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| year = {2026} |
| } |
| ``` |
|
|
| ## License |
|
|
| This dataset is licensed under the [Creative Commons Attribution-NonCommercial 4.0 International License](https://creativecommons.org/licenses/by-nc/4.0/). |
|
|
