@inproceedings{fell-etal-2018-lyrics,
    title = "Lyrics Segmentation: Textual Macrostructure Detection using Convolutions",
    author = "Fell, Michael  and
      Nechaev, Yaroslav  and
      Cabrio, Elena  and
      Gandon, Fabien",
    editor = "Bender, Emily M.  and
      Derczynski, Leon  and
      Isabelle, Pierre",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/C18-1174/",
    pages = "2044--2054",
    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."
}