Research InterestsSpeech Processing and Machine Learning for Mental State RecognitionIn the absence of a single characterization or measurable biological trait, the linguistic content of speech is used by clinicians as one measure of a variety of psychiatric conditions. However, due in part to a patient's impaired outlook and motivation; this information can be time consuming to gather and requires a large degree of skill and training to objectively assess. In recent years, the problem of automatically detecting and monitoring depression and suicidality using speech, more specifically non-verbal paralinguistic cues, has gained popularity. My work aims to investigate different vocal effects associated with the clinical profile of depression for the purpose of developing an automatic and objective classification or monitoring of mental state. Such a tool could be game changing in terms of patient monitoring; such as a smartphone application that provides immediate feedback and therapeutic mental health advice. This research has the potential to reduce the large socio-economic costs associated with depression and help improve the quality of life of someone suffering from or susceptible to mental illness. Specific Topics of Interests
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