<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">*** apologies for cross-posting *** Dear colleagues, We are calling for participation in the 9th Audio/Visual Emotion Challenge and Workshop (AVEC 2019), held as a workshop of ACM Multimedia 2019 in Nice, France (October 21). The challenge theme is on State-of-Mind, Depression with AI, and Cross-cultural emotion. For more information, see <a href="https://sites.google.com/view/avec2019/" class="">https://sites.google.com/view/avec2019/</a>. AVEC 2019 will be the ninth competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual, and audiovisual health and emotion analysis, with all participants competing under strictly the same conditions. We are calling for teams to participate in three Sub-Challenges: State-of-Mind Sub-Challenge (SoMS) The AVEC 2019 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. In the SoMS, self-reported mood (10-point Likert scale), after the narrative of personal stories (two positive and two negative), has to be predicted automatically from audio-visual recordings. Detecting Depression with AI Sub-Challenge (DDS) The AVEC 2019 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 patients interacting with a virtual agent conducting a clinical interview and driven by a human as a Wizard-of-Oz. The corpus contains new recordings with the virtual agent being, this time, wholly driven by artificial intelligence, i.e., without any human intervention. Those new recordings are used as a test partition for the DDS. Cross-cultural Emotion Sub-Challenge (CES) The AVEC 2019 CES is a 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: German culture => Hungarian culture. This dataset now includes data collected from new participants with Chinese culture, which is used as a test set for the AVEC 2019 CES. Challenge Registration <div class="">In order to participate in the Challenge, please register your team by using this form: <a href="https://forms.gle/QBxJMNA3igYZo61k8" class="">https://forms.gle/QBxJMNA3igYZo61k8</a>. Contributions</div><div class="">We encourage contributions aiming at highest performance w.r.t. the baselines provided by the organisers, and contributions aiming at finding new and interesting insights w.r.t. to the topic of these challenges, especially: - Audio/Video/Physiological-based Health/Emotion Recognition - Multimodal Representation Learning - Transfer Learning, Semi-supervised and Unsupervised Learning - Personalised Health/Emotion Recognition - Context in Health/Emotion Recognition - Cross-cultural and Holistic Recognition - Multiple Rater Ambiguity and Asynchrony <div class="">Prices</div><div class="">The sponsor of the AVEC 2019 Challenge, audEERING GmbH, and his partner Jabra, support the Challenge by offering one headphone to the winner of each Sub-challenge. 1) Detecting Depression with AI Sub-challenge: Jabra Elite 85h, 2) Cross-cultural Emotion Sub-challenge: Jabra Elite Active 65t, 3) State-of-Mind Sub-challenge: Jabra Elite 65t. Prices will be handed to the speaker of the winning contributions during the Workshop. </div><div class=""> </div>Important Dates Training and development sets available: April 29, 2019 Test sets available: June 11, 2019 Paper submission: July 2, 2019 (Anywhere on Earth) Notification of acceptance: August 5, 2019 Camera ready paper: August 12, 2019 Workshop: October 21, 2019 Kind regards, Fabien Ringeval on behalf of the AVEC 2019 organising committee Fabien Ringeval, Björn Schuller, Michel Valstar, Nicholas Cummins, Roddy Cowie, Maja Pantic</div></body></html>