2 research outputs found
Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations
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.Comment: 10 page
Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations
Due to COVID 19 pandemic, the 12th edition is cancelled. Next edition, the 13th, LREC 2022 will take place in Pharo on June 16-24, 2022.International audienceWe 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