The paper investigates how the annotators personality affects the result of their segmentation of unscripted speech into sentences. This task is inherently ambiguous and the disagreement between the annotators may result from a variety of factors – from speech disfluencies and linguistic properties of the text to social characteristics and the individuality of a speaker. While some boundaries are marked by the majority of annotators, there is also a substantial number of boundaries marked only by one or several experts. In this paper we focus on sentence boundaries that are only marked by a small number of annotators. We test the hypothesis that such “uncommon” boundaries are more likely to be identified by experts with particular personality traits. We found significant relationship between uncommon boundaries and two psychological traits of annotators measured by the Big Five personality inventory: emotionality and extraversion.
CITATION STYLE
Stepikhov, A., & Loukina, A. (2016). Low inter-annotator agreement in sentence boundary detection and annotator personality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9811 LNCS, pp. 461–468). Springer Verlag. https://doi.org/10.1007/978-3-319-43958-7_55
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