  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.
