Skip to Content
77 Mass Ave

Depression detector

Analyzing speech patterns can predict if a subject is depressed.
October 23, 2018
Illustration of person with speech bubble showing a brain within it.
Illustration of person with speech bubble showing a brain within it.
Illustration of person with speech bubble showing a brain within it.Ms. Tech; Face profile by Marek Polakovic, SK | Noun Project

To diagnose depression, clinicians interview patients, asking specific questions—about, say, past mental illnesses, lifestyle, and mood.

Machine learning that can detect words and intonations associated with depression could help with diagnostics. But such models tend to predict depression from the person’s specific answers to very specific questions.

A new neural-network model developed at MIT can be unleashed on raw text and audio data from interviews to discover speech patterns indicative of depression. Given a new subject, it can accurately predict whether the individual is depressed without needing any other information about the questions and answers.

“The model sees sequences of words or speaking style, and determines that these patterns are more likely to be seen in people who are depressed or not depressed,” says EECS graduate student and CSAIL researcher Tuka Alhanai, SM ’14, first author on a paper presented at the Interspeech conference. “Then, if it sees the same sequences in new subjects, it can predict if they’re depressed too.”

This research could lead to tools to detect signs of depression in natural conversation. For example, apps that alert users to signs of distress in their text and voice communications could be useful for those who can’t get to a clinician for diagnosis because of distance, cost, or lack of awareness that something may be wrong. The technology could also help identify mental distress during casual conversations in clinical offices. —

Keep Reading

Most Popular

transplant surgery
transplant surgery

The gene-edited pig heart given to a dying patient was infected with a pig virus

The first transplant of a genetically-modified pig heart into a human may have ended prematurely because of a well-known—and avoidable—risk.

open sourcing language models concept
open sourcing language models concept

Meta has built a massive new language AI—and it’s giving it away for free

Facebook’s parent company is inviting researchers to pore over and pick apart the flaws in its version of GPT-3

Muhammad bin Salman funds anti-aging research
Muhammad bin Salman funds anti-aging research

Saudi Arabia plans to spend $1 billion a year discovering treatments to slow aging

The oil kingdom fears that its population is aging at an accelerated rate and hopes to test drugs to reverse the problem. First up might be the diabetes drug metformin.

images created by Google Imagen
images created by Google Imagen

The dark secret behind those cute AI-generated animal images

Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.

Stay connected

Illustration by Rose WongIllustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.