Abstract
Depression is a serious illness that affects millions of people globally. From child to senior citizen are facing depression. Major area is occupied by adults, college going students and teenagers also. In recent years, the task of automation depression detection from speech has gained popularity. We provide a comparative analyses of various features for depression detection by evaluating how a system built on text-based, voice-based, and speech-based system. Detecting texts that express negativity in the data is one of the best ways to detect depression. In this paper, this problem of depression detection on social media and various machine learning algorithms that can be used to detect depression have been discussed. Key Words: Depression, Face detection, Audio detection, Video detection, Healthcare innovation, Result.
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