Emotion recognition is a significant research filed of pattern recognition and artificial intelligence.The Multimodal Emotion Recognition Challenge(MEC)is a part of the 2016 Chinese Conference on Pattern Recognition(CCPR).The goal of this competition is to compare multimedia processing and machine learning methods for multimodal emotion recognition.The challenge also aims to provide a common benchmark data set,to bring together the audio and video emotion recognition communities,and to promote the research in multimodal emotion recognition.The data used in this challenge is the Chinese Natural Audio-Visual Emotion Database(CHEAVD),which is selected from Chinese movies and TV programs.The discrete emotion labels are annotated by four experienced assistants.Three sub-challenges are defined: audio,video and multimodal emotion recognition.This paper introduces the baseline audio,visual features,and the recognition results by Random Forests.
Audio-visual corpus Features Multimodal fusion Challenge Emotion Affective computing
Ya Li Jianhua Tao Bj(o)rn Schuller Shiguang Shan Dongmei Jiang Jia Jia
Institute of Automation,Chinese Academy of Sciences,Beijing,Peoples Republic of China Institute of Automation,Chinese Academy of Sciences,Beijing,Peoples Republic of China;University of Chair of Complex and Intelligent Systems,University of Passau,Passau,Germany;Department of Computing Institute of Computing Technology,Chinese Academy of Sciences,Beijing,Peoples Republic of China Northwestern Polytechnical University,Xian,Peoples Republic of China Tsinghua University,Beijing,Peoples Republic of China