# Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations

arXiv: https://arxiv.org/abs/1912.02477 · HTML: https://mlsanity.com/paper/1912.02477/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Dec 2019.

## Built on by (most cited first, 3 of 3)

- [Positive and Risky Message Assessment for Music Products](https://mlsanity.com/paper/2309.10182/) (2023)
- [Language models for longitudinal analysis of abusive content in Billboard Music Charts](https://mlsanity.com/paper/2510.06266/) (2025)
- [The Contribution of Lyrics and Acoustics to Collaborative Understanding of Mood](https://mlsanity.com/paper/2207.05680/) (2022)

## Abstract (arXiv)

We present the WASABI Song Corpus, a large corpus of songs enriched with metadata extracted from music databases on the Web, and resulting from the processing of song lyrics and from audio analysis. More specifically, given that lyrics encode an important part of the semantics of a song, we focus here on the description of the methods we proposed to extract relevant information from the lyrics, such as their structure segmentation, their topics, the explicitness of the lyrics content, the salient passages of a song and the emotions conveyed. The creation of the resource is still ongoing: so far, the corpus contains 1.73M songs with lyrics (1.41M unique lyrics) annotated at different levels with the output of the above mentioned methods. Such corpus labels and the provided methods can be exploited by music search engines and music professionals (e.g. journalists, radio presenters) to better handle large collections of lyrics, allowing an intelligent browsing, categorization and segmentation recommendation of songs.