Computational Analysis of the Evolution of Atypical Language Caused by a Head Injury

Abstract

Sequelae of language disorder as a result of head injuries is a problem that, beyond remaining stable, tends to increase, according to evidence reported in different studies. Therefore, language impairments require interdisciplinary attention. From the perspective of Computational Science, aimed at providing information for a more precise characterization of these alterations, a solution involves different aspects. In particular, the limited data available due to the complexity in the collection of samples, the involved costs, or the insufficient availability of specialists. When alterations in language competences are the subject of study, data extension or augmentation techniques are not applicable. So with scarce data, prevailing data mining techniques are not appropriate to examine it. Therefore, in the present investigation an approach with alternative methods to study the data is proposed. We propose a trajectory representation of the narrative sample, after having identified the need to track the variability of the relationship among features over time. The aforementioned with the purpose of evaluating their contribution in the discrimination of language disorders analyzed, in addition to the aim of generating knowledge to comprehend language development.. The hypothesis that guides us is that, based on the study of the internal evolution of narrative instances, we can monitor this variability. The analysis of features as a path also leads us to develop a comparison process in terms of proximity. This as part of the formulation of a complete technique for tracking this variation in the relationship among features, which comprise the recovery period primarily for instances of the narrative task of retelling a story