Developing an app to detect depression based on changes in your voice

Scientists have revealed that they plan to create a smartphone application that detects whether a person is depressed based on changes in his voice. According to researchers at the University of Maryland, speech coordination changes when a person becomes depressed, and depressed people cannot think quickly, and Their speaking rate slows down with longer and longer pauses than if they were not depressed.

A voice detection application that uses deep learning, a type of machine learning based on artificial neural networks, can help discover such traits, which are often accurate. Mental health therapists can recommend the app to their patients, who send video and audio updates about their mood at home, which technology will then evaluate.

This would help patients and those around them stay informed about potentially life-threatening changes in their mental health, and the project is being led by Carol Espy Wilson, professor of electrical and computer engineering at the University of Maryland.

Professor Espy Wilson discusses how a person's mental health is reflected in the coordination of speech gestures, and the as-yet-unnamed app still in the initial planning stages, will be recommended by therapists to patients to help monitor them between therapy sessions.

Professor Esby Wilson said, the goal is to alert the therapist if the patient needs to be seen so that they do not become severely depressed and may decide to commit suicide."

The user logs into the app on their smartphone, which will then ask some basic questions about how they've been feeling physically and emotionally in the past week.

Users answer questions orally, their speech will be recorded, and the smartphone can also capture a video of the user as they speak if they choose to turn on the camera.