Profile-Based Text Classification for Children with Dyslexia

Profile-Based Text Classification for Children with Dyslexia

Chris Litsas (School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece), Maria Mastropavlou (Department of Philology, University of Ioannina, Ioannina, Greece) and Antonios Symvonis (School of Applied Mathematical and Physical Sciences, National Technical University of Athens, Athens, Greece)
DOI: 10.4018/ijmstr.2015010102
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Abstract

Although extensive research has been conducted in the field of text-readability and user modelling, scholars and researchers have taken into consideration only linguistic complexity in order to classify a text as readable or not. In this paper, the authors move one step forward by considering one more factor, namely intended reader's skills, and by trying to study text readability from a user-specific perspective. Central to our approach is the notion of the user's profile which carries information regarding the linguistic difficulties a user with dyslexia may experience. Based on the user's profile, they develop heuristics for evaluating text's readability for the specific user. The developed heuristics are incorporated in the text classification services of the iLearnRW project, aiming to facilitate the selection of appropriate/suitable reading resources, written in English or Greek, for children with dyslexia1.
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2. Linguistic Complexity And Reading Difficulty

Text readability is closely related to and even determined by the linguistic complexity of a text in the sense that the readability of a text increases as linguistic complexity decreases and vice versa. Therefore, linguistic complexity is a central notion when dealing with text classification.

Defining linguistic complexity is currently one of the most hotly debated notions in linguistics. In a first quantitative description of linguistic complexity, Blache (2011) identifies the types of constructions that are considered complex and thus difficult to process. She differentiates between local complexity, which refers to structural complexity, difficulty, which involves processing aspects and cognitive load, and global complexity, which refers to the language as a system rather than the complexity of a given realization (see Miestamo (2008) for a similar classification). Of the two levels, local complexity is considered measurable and has drawn considerable attention in the literature. Local complexity therefore includes phonological complexity (e.g. size of phonemic inventory, incidence of marked phonemes, phonotactic restrictions, maximum complexity of consonant clusters), morphological complexity (e.g. extent of allomorphy use and morphophonemic processes), syntactic complexity (e.g. level of clausal embedding and recursion), semantic and lexical complexity (e.g. extensive occurrence of homonymy and polysemy, type/token ratios), pragmatic complexity (e.g. degree of pragmatic inferencing) (see Szmrecsanyi and B. Kortmann (2012) for a review).

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