Abstract
The analysis of the different varieties of language alterations from several causes has become an indicator to support tentative diagnoses, not only physical but degenerative, functional or cognitive. In this study, we explore fluency-disfluency in language of participants after suffering a traumatic brain injury. From a linguistic-computational approach, covering one-year of periodic post-recovery stages samples, candidate subsets of features were evaluated with a pool of learning methods until obtaining comparable scores to a baseline taken as the maximums achieved with the same evaluation, but on the full feature set. Starting in three-months recovery stage, this was extended to six, nine, and twelve months. After setting a global overview during this period of the fluency response based on F1-score of the learning algorithms, the identified feature was the basis to work on a model in a longitudinal sense of the disfluency-response with dichotomous global linear mixed effects model.
Supported by CONACyT and partially by SNI.
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Roldán-Palacios, M., López-López, A. (2021). Disfluency as an Indicator of Cognitive-Communication Disorder Through Learning Methods. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds) Brain Informatics. BI 2021. Lecture Notes in Computer Science(), vol 12960. Springer, Cham. https://doi.org/10.1007/978-3-030-86993-9_5
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