Programme booklet (pdf)

PRESENTATION ABSTRACTS
Collecting and using a corpus of lyrics and their moods
Abstract
van Zaanen, Menno
Tilburg University
Recently, there has been an increase in availability of music in digital formats. This has
led to music collections that are different in nature than in the past. Collections are
typically larger and consist of a selection of individual pieces instead of complete
albums. Since playing any musical piece from the collection can be done without
physically changing the medium, listeners create playlists that allow them to identify a
subset of the collection and determine the order in which the pieces are played.
People creating playlists often want to group pieces based on their emotional load
(such as happy or sad). Creating such playlists, however, is time-consuming and
requires knowledge of the music in the collection, since emotional information is not
explicitly encoded with the pieces. We will describe a system that analyzes musical
pieces and, based on the lyrics, classifies them into their corresponding mood class.
This system is developed and evaluated using a corpus of lyrics of songs and their
corresponding mood. The mood tags were collected by social tagging of musical pieces
using the Moody iTunes plugin that is developed by the company Earth People within
the Crayon Room project. Starting from a list of artist, title and mood triples, the
corresponding lyrics of the songs have been collected. This has led to a corpus
containing the lyrics of 5,631 songs, which will be made publicly available.
Corresponding author: mvzaanen@uvt.nl
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