Song Lyrics Summarization Inspired by Audio Thumbnailing

Michael Fell, Elena Cabrio, Fabien Gandon, Alain Giboin


Abstract
Given the peculiar structure of songs, applying generic text summarization methods to lyrics can lead to the generation of highly redundant and incoherent text. In this paper, we propose to enhance state-of-the-art text summarization approaches with a method inspired by audio thumbnailing. Instead of searching for the thumbnail clues in the audio of the song, we identify equivalent clues in the lyrics. We then show how these summaries that take into account the audio nature of the lyrics outperform the generic methods according to both an automatic evaluation and human judgments.
Anthology ID:
R19-1038
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
328–337
Language:
URL:
https://www.aclweb.org/anthology/R19-1038
DOI:
10.26615/978-954-452-056-4_038
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/R19-1038.pdf