--- task_categories: - automatic-speech-recognition language: - en tags: - music - lyrics - evaluation - benchmark - transcription pretty_name: MUSDB-ALT license: cc-by-nc-sa-4.0 dataset_info: features: - name: name dtype: string - name: text dtype: string - name: text_tagged dtype: string - name: lines list: - name: start dtype: float64 - name: end dtype: float64 - name: text dtype: string - name: text_tagged dtype: string splits: - name: test num_bytes: 141507 num_examples: 39 download_size: 80501 dataset_size: 141507 configs: - config_name: default data_files: - split: test path: data/test.jsonl --- # Dataset Card for MUSDB-ALT This dataset contains long-form lyric transcripts following the Jam-ALT [guidelines](https://huggingface.co/datasets/jamendolyrics/jam-alt/blob/main/GUIDELINES.md) for the test set of the dataset [MUSDB18](https://sigsep.github.io/datasets/musdb.html), with line-level timings. There are two versions of each transcript at the song and line level - `text` contains the normal transcript, and `text_tagged` contains the transcript with non-lexical vocables enclosed in tags `` and ``. ## Dataset Details The dataset was constructed manually, based on the [MUSDB18 lyrics extension](https://zenodo.org/records/3989267) as a starting point. The lyrics extension contains transcripts of the 45 English language songs out of the 50 in the MUSDB18 test set. We annotated 39 of those 45 songs, excluding 6 for the following reasons: - Signe Jakobsen - What Have You Done To Me : Three overlapping vocal lines that could not be separated into lead and backing vocals - PR - Happy Daze : Vocal content primarily from highly processed vocal samples - PR - Oh No : Vocal content primarily from highly processed vocal samples - Skelpolu - Resurrection : Vocal content primarily from highly processed vocal samples - Timboz - Pony : Lyrics unintelligble due to screamed enunciation style - Triviul feat The Fiend - Widows : Three overlapping vocal lines that could not be separated into lead and backing vocals ### Dataset Description **Paper:** The dataset was introduced in the paper [Exploiting Music Source Separation for Automatic Lyrics Transcription with Whisper"](https://arxiv.org/abs/2506.15514) published at the Workshop [Artificial Intelligence For Music](https://ai4musicians.org/2025icme.html) at ICME 2025 - **Funding:** This work was supported by InnovateUK \[Grant Number 1010280\] - **License:** https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en ## Citation **BibTeX:** ``` @inproceedings{syed-2025-mss-alt, author = {Jaza Syed and Ivan Meresman-Higgs and Ond{\v{r}}ej C{\'{\i}}fka and Mark Sandler}, title = {Exploiting Music Source Separation for Automatic Lyrics Transcription with {Whisper}}, booktitle = {2025 {IEEE} International Conference on Multimedia and Expo Workshops (ICMEW)}, publisher = {IEEE}, year = {2025}, note = {In press} } ```