@inproceedings{georgescul-etal-2007-exploiting,
    title = "Exploiting structural meeting-specific features for topic segmentation",
    author = "Georgescul, Maria  and
      Clarck, Alexander  and
      Armstrong, Susan",
    editor = "Hathout, Nabil  and
      Muller, Philippe",
    booktitle = "Actes de la 14{\`e}me conf{\'e}rence sur le Traitement Automatique des Langues Naturelles. Articles longs",
    month = jun,
    year = "2007",
    address = "Toulouse, France",
    publisher = "ATALA",
    url = "https://aclanthology.org/2007.jeptalnrecital-long.1",
    pages = "15--24",
    abstract = "In this article we address the task of automatic text structuring into linear and non-overlapping thematic episodes. Our investigation reports on the use of various lexical, acoustic and syntactic features, and makes a comparison of how these features influence performance of automatic topic segmentation. Using datasets containing multi-party meeting transcriptions, we base our experiments on a proven state-of-the-art approach using support vector classification.",
}