Speech Recognition-Based Prediction for Mental Health and Depression: A Review

A person with a mental disorder exhibits a significant disturbance in his or her behavior. Generally, mental disorders are associated with distress or impairment of normal functioning. Lack of adequate resources and facilities, as well as a lack of awareness of the symptoms of mental illness, prevent people from getting the help they need. The ability to assess depression through speech is a critical factor in improving the diagnosis and treatment of depression. The spoken language is said to provide access to the mind, and a wide range of speech capture and processing technologies can be used to analyze mental health. Speech processing is about recognizing spoken words. The automatic recognition and extraction of information from speech enables the determination of some physiological characteristics that make a speaker unique to identify their mental health status. In this paper, we describe how mental health-related problems can be predicted by speech processing. This paper identifies the gaps in the literature review that lead to the proposed methodology.