You are here

Multimodal Emotion Recognition for AVEC 2016 Challenge

Authors: 

Filip Povolny, Pavel Matejka, Michal Hradis, Anna Popková, Lubomir Otrusina, Pavel Smrz, Ian Wood, Cécile Robin, Lori Lamel

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
This paper describes a systems for emotion recognition and its application on the dataset from the AV+EC 2016 Emotion Recognition Challenge. The realized system was produced and submitted to the AV+EC 2016 evaluation, making use of all three modalities (audio, video, and physiological data). Our work primarily focused on features derived from audio. The original audio features were complement with bottleneck features and also text-based emotion recognition which is based on transcribing audio by an automatic speech recognition system and applying resources such as word embedding models and sentiment lexicons. Our multimodal fusion reached CCC=0.855 on dev set for arousal and 0.713 for valence. CCC on test set is 0.719 and 0.596 for arousal and valence respectively.
Conference Name: 
ACM-Multimedia 2016
Proceedings: 
Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge
Digital Object Identifer (DOI): 
10.1145/2988257.2988268
Publication Date: 
16/10/2017
Pages: 
75-82
Research Group: 
Institution: 
National University of Ireland, Galway (NUIG)
Open access repository: 
Yes
Publication document: