(Springer, 2021-9-18)
Lopez De Luise, Maria Daniela; Saad, Ben Raúl; Ibacache, Tiago; Saliwonczyk Carballo, Christian; Pescio, Pablo; Soria, Lucas
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.