The Influence of the Voice Acquisition Method to the Mental Health State Estimation Based on Vocal Analysis

Mental health disorders have become a social problem, and countermeasures are thus required. Previously, the authors developed the MIMOSYS (Mind Monitoring System) algorithm to evaluate an individual’s mental health state using their voice. An individual’s mental health state is detected using aspects of emotions that are present in their voice; however, since emotions change subtly, influence to emotions will be concerned owing to voice acquisition methods such as a natural conversation with someone else or reading fixed phrases. The aim of this research was to evaluate the influence of the type of voice acquisition method on the estimation of emotion and mental health state using the vocal analysis in MIMOSYS. In the experiments, we collected emotions and MIMOSYS analysis results from voice recordings during calls and during readings of fixed phrases from the application for over two weeks. In addition, the Beck’s Depression Inventory (BDI) test was used to evaluate participants’ subjective depression levels at the beginning of the experiment. In the evaluation, we analyzed recordings of calls and readings of fixed phrases for the participants in the normal range of the BDI test. Results indicated that the expression of emotions was suppressed in the recordings of readings of fixed phrases when compared to the recordings of calls, and the analysis result by MIMOSYS tended to be lower. Consequently, when measuring an individual’s mental health state from their voice, it may be necessary to match the type of voice acquisition methods or correct the estimations according to acquisition method.