Abstract

Abstract—Currently, over 300 million people worldwide suffer from depression disorders to varying degrees. Including social stigma, treatment cost and availability, might prevent affected individuals from seeking help. 60 percent of those affected by mental illnesses do not receive treatment. So to overcome this problem the project aimed to be identifying the person suffers from depression and the root problem. As the system gets trained by the inputs given by the user, it starts customizing the recommendation and responses that address the root cause. Keywords— Machine Learning, depression prediction, speech to text, text to speech, Data cleaning, Data Normalization, Data collection, SVM classifier