Mok, W.T., Sing, R, Jiang, X. and See, S.L. (2014), “Proposal of a Depression Detector”, Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2014), pp 1-5, 9–12 December 2014, Cambodia. doi: 10.1109/APSIPA.2014.7041742
Abstract:
Rapid advancements in technology, coupled with the increasingly widespread usage of social media, has brought about various impacts on our psychological health. Past research has been conducted on Singaporeans and ascertained the relationship between frequency of social media usage and depression levels in teenage girls. This research aims to investigate the relationship between depression and voice characteristics namely pitch, loudness and number of pauses, so as to determine markers for depression. The markers were then incorporated into a smartphone game designed to detect depression level through voice analysis. The likelihood of an individual suffering from depression was found to increase with loudness and frequency of pauses and to decrease with the frequency of an individual's voice. A mock up of the smartphone application was created on Justinmind and Powerpoint
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