A computational model for speech disorders using problematic phonemes with ontological reasoning

This work presents a method for data gathering to construct a corpus related to speech disorders in children; such corpus will serve as the base to generate some semi-automatic ontologies, in order to become a computational model to support therapists for diagnosis and possible treatment. Speech disorders, phonemes and some additional information are classified using taxonomies obtained from speech disorders specialized literature. Based on the obtained taxonomies, the ontologies, which structure and formalize concepts defined by the main topic authors, are developed. The ontologies are constructed following some parts of classic methodologies and their subsequent validation is made through competency questions. The development of the model is based on Natural Language Processing (NLP) and Information Retrieval (IR) techniques. Integration of the ontologies is made to be able to make a classification based in problematic phonemes; this is suggested as a complement to the diagnostic tool in the model.