Lyrics Segmentation: Textual Macrostructure Detection using Convolutions

Michael Fell 1 Yaroslav Nechaev Elena Cabrio 2 Fabien Gandon 2
2 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
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.
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Michael Fell, Yaroslav Nechaev, Elena Cabrio, Fabien Gandon. Lyrics Segmentation: Textual Macrostructure Detection using Convolutions. Conference on Computational Linguistics, Aug 2018, Santa Fe, New Mexico, United States. pp.2044-2054. ⟨hal-01883561⟩

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