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

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Abstract

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 recommendation of songs. We provide the files of the current version of the WASABI Song Corpus, the models we have built on it as well as updates here: https://github.com/micbuffa/WasabiDataset.
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Dates and versions

hal-03133188 , version 1 (05-02-2021)

Identifiers

  • HAL Id : hal-03133188 , version 1

Cite

Michael Fell, Elena Cabrio, Elmahdi Korfed, Michel Buffa, Fabien Gandon. Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations. LREC 2020 - 12th edition of the Language Resources and Evaluation Conference, May 2020, Marseille, France. ⟨hal-03133188⟩
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