Scientists find new way to detect depression from speech

Credit: Engin Akyurt /Unsplash.

Artificial intelligence (AI) tools have achieved promising results on numerous tasks and could soon assist professionals in various settings.

In recent years, computer scientists have been exploring the potential of these tools for detecting signs of different physical and psychiatric conditions.

In a study from Jinhua Advanced Research Institute and elsewhere, scientists found AI could help detect depression from speech.

They developed a deep learning algorithm that could detect depression from a person’s speech.

This model was trained to recognize emotions in the human speech by analyzing different relevant features.

In the study, researchers trained their model on the DAIC-WOZ dataset, a collection of audio and 3D face expressions of patients diagnosed with depressive disorder and of people without depression.

These audio recordings and facial expressions were collected during interviews led by a virtual agent, who asked different questions about the interviewee’s mood and life.

To extract relevant features from voice recordings, the team’s model uses OpenSmile (open-source speech and music interpretation by large-space extraction).

This is a toolkit often used by computer scientists to extract features from audio clips and classify these clips.

The researchers used this tool to extract individual speech features and combinations of features that are commonly found in the speech of patients diagnosed with depression.

Subsequently, they used a technique to reduce the set of features that they extracted.

The team evaluated their model in a series of tests, where they assessed its ability to detect depressed and non-depressed people from recordings of their voices.

Their framework achieved remarkable results, detecting depression with an accuracy of 87% in male patients and 87.5% in female patients.

In the future, the deep learning algorithm developed by this team of researchers could be an additional assistive tool for human psychiatrists and doctors, along with other well-established diagnostic tools.

In addition, this study could inspire the development of similar AI tools for detecting signs of psychiatric disorders from speech.

If you care about depression, please read studies about vegetarianism linked to a higher risk of depression, and Vitamin D could help reduce depression symptoms.

For more information about brain health, please see recent studies that ultra-processed foods may make you feel depressed, and flavonoid-rich foods could help prevent dementia.

The study was conducted by Han Tian et al and published in Mobile Networks and Applications.

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