Autistic Verbal Behavior Language Parameterization

Abstract

In severe degrees of ASD (Autistic Spectrum Disorder), patients are not able to produce or understand natural language, and they also have social disorders that make it difficult the communication with other people. Their natural language presents different degrees of alteration, reaching in some cases the impossibility of speaking. This chapter presents an approach to model the patient’s behavior by processing recordings during the therapy. Video and audio data provide certain hidden patterns as we already presented in previous work. By using Machine Learning, it is possible to obtain a customized model that makes it possible to evaluate the individual’s performance during his interaction with other people. The model inputs a specific set of stereotyped responses collected in a systematic way, labeled as patterns. Those movements and sounds, represents how patterns in audio and video relate to stimuli from the environment. Findings allow to discriminate when and how there is a reaction, an autistic verbal behavior.