Clinical depression is a major risk factor in suicides and is associated with high mortality rates, therefore making it one of the leading causes of death worldwide every year. Symptoms of depression often first appear during adolescence at a time when the voice is changing, in both males and females, suggesting that specific studies of these phenomena in adolescent populations are warranted. The properties of acoustic speech have previously been investigated as possible cues for depression in adults. However, these studies were restricted to small populations of patients and the speech recordings were made during patient’s clinical interviews or fixed-text reading sessions. A collaborative effort with the Oregon research institute (ORI), USA allowed the development of a new speech corpus consisting of a large sample size of 139 adolescents (46 males and 93 females) that were divided into two groups (68 clinically depressed and 71 controls). The speech recordings were made during naturalistic interactions between adolescents and parents. Instead of covering a plethora of acoustic features in the investigation, this study takes the knowledge based from speech science and groups the acoustic features into five categories that relate to the physiological and perceptual areas of the speech production mechanism. These five acoustic feature categories consisted of the prosodic, cepstral, spectral, glottal and Teager energy operator (TEO) based features. The effectiveness in applying these acoustic feature categories in detecting adolescent’s depression was measured. The salient feature categories were determined by testing the feature categories and their combinations within a binary classification framework. In consistency with previous studies, it was observed that: - there are strong gender related differences in classification accuracy; - the glottal features provide an important enhancement of the classification accuracy when combined with other types of features; An important new contribution provided by this thesis was to observe that the TEO based features significantly outperformed prosodic, cepstral, spectral, glottal features and their combinations. An investigation into the possible reasons of such strong performance of the TEO features pointed into the importance of nonlinear mechanisms associated with the glottal flow formation as possible cues for depression
