Abstract
Automatic detection of depression has attracted increasing attention from researchers in psychology, computer science, linguistics, and related disciplines. As a result, promising depression detection systems have been reported. This paper surveys these efforts by presenting the first cross-modal review of depression detection systems and discusses best practices and most promising approaches to this task.
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CITATION STYLE
Morales, M. R., Scherer, S., & Levitan, R. (2017). A cross-modal review of indicators for depression detection systems. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 1–12). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-3101
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