For many speech and language disorders in children today, the detection process of such developmental disorders is lengthy and difficult, inhibiting children from being diagnosed earlier. In our project, we will analyze and extract features from speech samples from different children with developmental language/speech disorders and normal development. We will use these extracted features and machine learning techniques to train a classifier to detect children with risk for specific speech and language developmental disorders. Our classifier would serve as a simple, fast prescreening technique that can be used to identify children at risk for such developmental disorders.

Prior to coming to MIT, I planned to study biomedical engineering. Now that I am studying computer science, I still wish to meld my previous interests with my current studies. After taking 6.034 with Professor Winston, I wanted to delve into the field of machine learning. I am very excited for this SuperUROP project because it is the combination of all my interests!