@inproceedings{mckee-etal-2020-towards,
    title = "Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data",
    author = {McKee, Gabriel  and
      Macoir, Jo{\"e}l  and
      Gagnon, Lydia  and
      Tremblay, Pascale},
    editor = "Dipper, Stefanie  and
      Zeldes, Amir",
    booktitle = "Proceedings of the 14th Linguistic Annotation Workshop",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.law-1.15/",
    pages = "160--166",
    abstract = "We propose a new method for annotating verbal fluency data, which allows the reliable detection of the age-related decline of lexical access capacity. The main innovation is that annotators should inferentially assess the intention of the speaker when producing a word form during a verbal fluency test. Our method correlates probable speaker inten-tions such as ``intended as a valid answer'' or ``intended as a meta-comment'' with lin-guistic features such as word intensity (e.g. reduced intensity suggests private speech) and syntactic integration. The annotation scheme can be implemented with high reliabil-ity, and minimal linguistic training. When fluency data are annotated using this scheme, a relation between fluency and age emerges; this is in contrast to a strict implementation of the traditional method of annotating verbal fluency data, which has no way of deal-ing with score-confounding phenomena because it force-groups all verbal fluency pro-ductions {--}regardless of speaker intention{---} into one of three taxonomic groups (i.e. val-id answers, perseverations, and intrusions). The traditional lack of fine-grained annota-tion units is especially problematic when analyzing the qualitatively distinct fluency da-ta of older participants and may cause studies to miss the relation between lexical access capacity and age."
}