“…A comparative study (Alghowinem, Goecke, Wagner, Epps et al, ) using acoustic and prosodic features to detect depression in spontaneous speech found that voice features such as intensity, root mean square and loudness perform best to detect depression in the data set. Other studies (Dham, Sharma, & Dhall, ; Kandsberger, Rogers, Zhou, & Humphris, ; Lopez‐Otero, Docio‐Fernandez, Abad, & Garcia‐Mateo, ; Salekin, Eberle, Glenn, Teachman, & Stankovic, ; Scherer, Morency, Gratch, & Pestian, ) also exploited different machine learning techniques and suggested that the speech can be effectively utilised to detect distress and related conditions.…”