State-of-Mind, Depression, and Cross-cultural Affect
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Depression, and Cross-cultural Affect" is a satellite event of ACM MM 2019, and the ninth competition aimed at comparison of multimedia processing machine learning methods for automatic audio, visual, and audio-visual health and emotion sensing, with all participants competing under strictly the same conditions.
There are three sub-challenges:
The SoMS is a new task focusing on the continuous adaptation of human state-of-mind (SOM), which is pivotal for mental functioning and behaviour regulation. Human SOM constantly shifts due to internal and external stimuli, and habitual use of either adaptive or maladaptive SOM influences mental health. One key aspect of the human experience is our emotions, as they reflect our SOM. In the SoMS, self-reported mood (10-point Likert scale), before and after the narrative of personal stories (two positive and two negative), has to be predicted automatically from audio-visual recordings (USoM corpus). Performance is evaluated with the Concordance Correlation Coefficient (CCC).
The DDS is a major extension of the AVEC 2016 DSC, where the level of depression severity (PHQ-8 questionnaire) was assessed from audio-visual recordings of US Army veterans interacting with a virtual agent conducting a clinical interview and driven by a human as a Wizard-of-Oz (DAIC-WOZ corpus). The DAIC corpus contains new recordings of US Army veterans with the virtual agent being, this time, fully driven by artificial intelligence, i.e., without any human intervention. Those new recordings are used as a test partition for the DDS and will help to understand how the absence of a human for conducting the virtual agent impacts on automatic depression severity assessment. Performance is evaluated with the Concordance Correlation Coefficient (CCC).
The CES is major extension of the AVEC 2018 CES, where dimensions of emotion were inferred from audio-visual recordings collected "in-the-wild", i.e., with standard webcams and at home/work place, in a cross-cultural setting. (e.g. German culture => Hungarian culture (SEWA corpus)). This dataset now indicates data collected from new participants with Chinese culture, which is used as a test set for the AVEC 2019 CES to investigate how emotion knowledge of Western European cultures can be transferred to the Chinese culture. Performance is evaluated with the Concordance Correlation Coefficient (CCC) averaged over the emotion dimensions.