Cross-cultural depression recognition from vocal biomarkers

Sharifa Alghowinem, Roland Goecke, Julien Epps, Michael Wagner, Jeffrey Cohn

    Research output: Contribution to journalConference articlepeer-review

    33 Citations (Scopus)

    Abstract

    No studies have investigated cross-cultural and cross-language characteristics of depressed speech. We investigated the generalisability of a vocal biomarker-based approach to depression detection in clinical interviews recorded in three countries (Australia, the USA and Germany), two languages (German and English) and different accents (Australian and American). Several approaches to training and testing within and between datasets were evaluated. Using the same experimental protocol separately within each dataset, (cross-classification) accuracy was high.combining datasets, high accuracy was high again and consistent across language, recording environment, and culture. Training and testing between datasets, however, attenuated accuracy. These finding emphasize the importance of heterogeneous training sets for robust depression detection.

    Original languageEnglish
    Pages (from-to)1943-1947
    Number of pages5
    JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
    Volume08-12-September-2016
    DOIs
    Publication statusPublished - 2016
    Event17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 - San Francisco, United States
    Duration: 8 Sept 201616 Sept 2016

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