Lincoln Laboratory team takes honors at Audio/Visual Emotion Challenge and Workshop

A team from MIT Lincoln Laboratory's Bioengineering Systems and Technologies Group was named a first-place subchallenge winner at the 2014 Audio/Visual Emotion Challenge and Workshop (AVEC 2014), the fourth annual competition that invites participants to use multimedia processing and machine learning to analyze subjects' emotional states or estimate subjects' level of depression. Held at the annual Association for Computing Machinery (ACM) International Conference on Multimedia, the challenge gauges the success of entrants' approaches to automated emotion detection on a set of common benchmarks. In 2014, two subchallenges were presented: continuously distinguishing emotions and estimating the level of subjects' depression from audio and visual data. Of the 14 groups competing in the 2014 depression assessment subchallenge, Lincoln Laboratory's team was the most successful in predicting a depression score. Participants in this subchallenge estimate the severity of subjects' depression from either vocal characteristics detected in audio or facial signs identified in video recordings, or both.