README.md

---
license: other
license_name: per-track-cc
license_details: >-
  Word timing annotations derive from JamendoLyrics and carry each song's
  original Creative Commons license (BY / BY-SA / BY-ND / BY-NC / BY-NC-SA /
  BY-NC-ND — see the `license` field per record). Difficulty bucket
  annotations (buckets.csv) are original work released under CC-BY-4.0.
  Audio is NOT redistributed here; fetch it from the jamendolyrics dataset.
task_categories:
- automatic-speech-recognition
language:
- en
- fr
- de
- es
tags:
- music
- lyrics
- alignment
- singing
- benchmark
- evaluation
pretty_name: signalign-bench
size_categories:
- n<1K
---

# signalign-bench v0.1

**The first difficulty-bucketed word-level lyrics alignment benchmark for
sung vocals.**

Existing lyrics-alignment evaluation reports one blended number. Singing
fails aligners in *different ways* — fast rap, melisma, held notes, vocals
buried in the mix — and a single number hides all of it. This benchmark
tags every track with its dominant difficulty and reports metrics per
bucket.

Maintained at: https://github.com/alcadramin/signalign (evaluation harness,
baselines, protocol).

## Contents

| File | What |
|---|---|
| `jamendolyrics.jsonl` | 79 tracks, word-level gold onsets/offsets, difficulty bucket, language, per-track license |
| `buckets.csv` | The raw human bucket annotations (id → difficulty) |
| `results/` | Baseline system scores (raw JSON, per bucket) |

Schema per record: `id`, `audio_path` (relative to the
[jamendolyrics](https://huggingface.co/datasets/jamendolyrics/jamendolyrics)
dataset root), `duration`, `words[{text,start,end}]`, `difficulty`,
`language`, `source`, `license`.

## Difficulty buckets

Assigned by ear by a human annotator (single annotator, v0.1 — annotator:
alca, 2026-08-14). One dominant label per track; ties broken by fixed
priority rap > melisma > held > buried.

| bucket | tracks | meaning |
|---|---|---|
| clean | 46 | clear vocal, plain delivery |
| buried | 13 | vocal low in the mix / heavy accompaniment |
| rap | 11 | fast dense delivery |
| melisma | 5 | multi-pitch syllables, vocal runs |
| held | 4 | delivery built from long sustained notes |

## Audio

Not re-hosted. Word timings and buckets reference the
[jamendolyrics/jamendolyrics](https://huggingface.co/datasets/jamendolyrics/jamendolyrics)
dataset (same track ids / file names):

```bash
hf download jamendolyrics/jamendolyrics --repo-type dataset --local-dir data/jamendolyrics
```

Note: top-level `mp3/` entries in that download may materialize as text
pointer files; real audio lives under `subsets/<lang>/mp3/`.

## Metrics protocol

Defined and implemented in
[`eval/score.py`](https://github.com/alcadramin/signalign) (single source
of truth): per-bucket **coverage**, **MAE**, **MedAE** (matched words, ms),
**PCO@{100,200,300}ms** with all gold words as denominator (a dropped word
counts as a miss). Word matching = LCS over normalized text.

## Baseline results (v0.1)

Demucs htdemucs vocal stem → forced alignment. Full tables in `results/`.

| system | lyrics input | coverage | MAE | MedAE | PCO@100 |
|---|---|---|---|---|---|
| wav2vec2-base-960h (speech) + gold lyrics | yes | 1.00 | 150ms | 41ms | 79.7% |
| WhisperX medium (ASR path) | no | 0.56 | 2187ms | 54ms | 38.9% |

Per-bucket highlights: rap fails catastrophically not gradually (42ms MedAE,
214ms MAE, lyrics-informed); melisma smears onsets (worst PCO@100); held
notes are the easiest bucket, not the hardest; WhisperX drops 44% of sung
words. Whisper language ID misdetected a German rap track as Khmer.

## Limitations

- Single annotator, track-level buckets (v0.2 targets segment-level).
- 79 tracks, 4 European languages; no extreme-technique or a-cappella-rap
  hard cases yet (planned additions).
- Baseline alignments use an English character vocabulary after ASCII
  folding for all languages.

## Citation

```
@misc{signalign-bench,
  title = {signalign-bench: a difficulty-bucketed word-level lyrics
           alignment benchmark for sung vocals},
  author = {alca},
  year = {2026},
  url = {https://huggingface.co/datasets/Alcadramin/signalign-bench}
}
```

Please also cite the underlying JamendoLyrics dataset (Stoller et al.;
Durand et al., see the jamendolyrics dataset card).