App to analyze your speech and mental health

Researchers from the University of Maryland in US showed that for a person, as his feeling of depression grow worse, his certain vocal features also changes accordingly. Scientists said that rather than leaning only on patients' self-report, a new smartphone app can analyze the patients' speech so as to gain correct information about patients' mental health.

 The app could keep an eye upon physical as well as psychological symptoms of mental illness on a regular basis. Furthermore, it also provide both patients and their mental health providers with feedback about their status.


By analyzing a data set collected from a 2007 study, physicists Carol-Espy-Wilson and her colleagues made a quantitative experiment on the vocal characteristics of depression. The study evaluated patients' depression levels each week using the Hamilton Depression Scale and then recorded them speaking freely about their day.

The researchers used data from six patients who, over the six-week course of the previous study, had registered as depressed some weeks and not depressed other weeks. 

They compared these patients' Hamilton scores with their speech patterns each week, and found a statistics between depression and certain curing properties. 

When patients' feelings of depression were worst, their speech tended to be breathier and slower. 

The team also found increases in noise and shimmer, two measures of acoustic disturbance that measure the frequency and amplitude variation of the sound, respectively. Speech high in jitters and shimmer tends to sound rough. 

Espy-Wilson hopes the interactive technology will appeal to teens and young adults, a particularly vulnerable group for mental health problems. 

"Their emotions are all over the place during this time, and that's when they're really at risk for depression. We have to reach out and figure out a way to help kids in that stage," she said. 

The researchers plan to repeat the study in a larger population, this time comparing speech patterns in individuals with no history of mental illness to those with depression to create an acoustic profile of depression-typical speech. 

A phone app could use this information to analyze patients' speech, identify acoustic signatures of depression and provide feedback and support. 

Sometimes, patients might not recognize or be willing to admit that they are depressed. By receiving regular feedback based on acoustical and other measurements, they might learn to self-monitor their mental states and recognize when they should seek help. 

The technology could also promote communication between therapists and patients, allowing for continuous, responsive care in addition to regular in-person appointments.