Continuous Monitoring of Emotions by a Multimodal Cooperative Sensor System. (2015)

• Record Type: Journal Article
• Authors: Mencattini, Arianna; Ringeval, Fabien; Schuller, Björn; Martinelli, Eugenio; Di Natale, Corrado
• Is Part Of: Procedia engineering. Volume 120(2015)
• Page Start: 556
• Page End: 559
• Publication Date: 2015
• Subjects: Speech emotion recognition -- multimodal cooperative sensorial systems -- naturalistic emotional display; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2015.08.716
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: Multimodal emotion recognition is a challenging topic that aims at determining the affective state of a subject by combining audio-visual and physiological signals acquired in a naturalistic environment. This procedure can be used to monitor the emotional state of a subject affected by mental disorder or under medical treatment. Common attempts principally learn a unique complex machine learning system on descriptors collected from different subjects. The novel paradigm of single-subject multimodal regression model (SSMRM) that we propose in this study is embedded in a averaging-based merging strategy that aggregates the responses provided by each model during the test of a new subject. This new approach presents a flexible architecture able to continuously embed new models without global re-training.