Visualizing health with EMO3on polarity history using voice

Abstract

Maintaining mental health as well as physical health is essential for our daily lives. We think that we could use a “mood” meter every day or regularly to see our own mental health condition similarly as in the case of weight meters. When performing emotion recognition using human speech, one of linguistic information and prosodic features included in speech is often used. However, by capturing both sides of speech, which is a means of human communication, it is considered that emotion recognition can be more accurately realized. Based on the background, we have developed PNViz, Positive-and-Negative Polarity Visualizer, an application running on an Android phone, to show the state of positive-ness of mental health by recording a short voice message. PNViz consists of the smartphone application and an analyzing server where the recorded voice is processed with both lexical and phonetic analyses and calculates a score ranging from -1 to 1. The calculated score is continuously logged and shown to the user and thus it is expected to encourage the user to take refreshing breaks or holidays.