Lyrics Segmentation: Textual Macrostructure Detection using Convolutions

Michael Fell, Yaroslav Nechaev, Elena Cabrio, Fabien Gandon


Abstract
Lyrics contain repeated patterns that are correlated with the repetitions found in the music they accompany. Repetitions in song texts have been shown to enable lyrics segmentation – a fundamental prerequisite of automatically detecting the building blocks (e.g. chorus, verse) of a song text. In this article we improve on the state-of-the-art in lyrics segmentation by applying a convolutional neural network to the task, and experiment with novel features as a step towards deeper macrostructure detection of lyrics.
Anthology ID:
C18-1174
Volume:
Proceedings of the 27th International Conference on Computational Linguistics
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2044–2054
Language:
URL:
https://www.aclweb.org/anthology/C18-1174
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/C18-1174.pdf