AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge

TL;DR

The AVEC 2016 challenge provides a standardized benchmark for comparing multimedia processing and machine learning methods in depression and emotion recognition using audio, visual, and physiological data.

Contribution

It introduces a common dataset, evaluation framework, and baseline results for multi-modal depression and emotion analysis, fostering community collaboration.

Findings

Baseline system performance established for two tasks.

Comparison of different approaches under uniform conditions.

Insights into the benefits of multi-modal data fusion.

Abstract

The Audio/Visual Emotion Challenge and Workshop (AVEC 2016) "Depression, Mood and Emotion" will be the sixth competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and physiological depression and emotion analysis, with all participants competing under strictly the same conditions. The goal of the Challenge is to provide a common benchmark test set for multi-modal information processing and to bring together the depression and emotion recognition communities, as well as the audio, video and physiological processing communities, to compare the relative merits of the various approaches to depression and emotion recognition under well-defined and strictly comparable conditions and establish to what extent fusion of the approaches is possible and beneficial. This paper presents the challenge guidelines, the common data used, and the performance of the baseline system on the two tasks.