theelderemo/genius-lyrics-cleaned

A heavily cleaned, English-only, genre-filtered subset of the Genius Song Lyrics with Language Information Kaggle dataset. Reduced from 9+ GB to 2.56 GB through language filtering, genre filtering, artifact removal, and deduplication. Optimized for language model fine-tuning, lyric generation, and music NLP research.

This dataset ships as a single train split. You should create validation and test splits appropriate to downstream task

The raw Genius dataset contains millions of song entries across dozens of languages, genres, and quality levels — including non-music content like poetry, book excerpts, and miscellaneous text tagged as misc. This cleaned version retains only English-language songs from verified music genres, with lyrics scrubbed of Genius UI artifacts, HTML residue, and duplicates. The result is a high-signal corpus suitable for causal language model pretraining or supervised fine-tuning on lyric generation tasks.

The following steps were applied in order:

1. Language filter — Retained only rows where language == 'en', removing all non-English entries.
2. Genre filter — Dropped the misc tag (which contains books, poems, speeches, and other non-music content). Retained only the 15 confirmed music genre tags listed below.
3. Artifact removal — Applied regex cleaning to remove:
   • Genius embed counters (e.g., 1234Embed at end of lyrics)
   • UI strings like "See [Artist] Live", "Get tickets", "You might also like"
   • Residual HTML tags (<...>)
4. Section header normalization — Simplified attributed headers: [Chorus: Cam'ron & Jay-Z] → [Chorus], preserving verse structure while removing contributor meta.
5. Whitespace normalization — Collapsed 3+ consecutive newlines to 2, and collapsed horizontal whitespace.
6. Stub removal — Dropped any entry whose cleaned lyrics are under 100 characters.
7. Exact deduplication — Removed entries with identical cleaned lyrics.
8. Near-deduplication — For entries sharing the same artist + title, retained the version with the highest view count.

If you use this dataset in research or a project, please cite both the upstream Kaggle source and this repository:

@misc{christopher_dickinson_2026,
    author       = { Christopher Dickinson },
    title        = { genius-lyrics-cleaned (Revision 9742989) },
    year         = 2026,
    url          = { https://huggingface.co/datasets/theelderemo/genius-lyrics-cleaned },
    doi          = { 10.57967/hf/7978 },
    publisher    = { Hugging Face }
}