Perception of Blended Emotions: From Video Corpus to Expressive Agent

Abstract. Real life emotions are often blended and involve several simultane-ous superposed or masked emotions. This paper reports on a study on the per-ception of multimodal emotional behaviors in Embodied Conversational Agents. This experimental study aims at evaluating if people detect properly the signs of emotions in different modalities (speech, facial expressions, gestures) when they appear to be superposed or masked. We compared the perception of emotional behaviors annotated in a corpus of TV interviews and replayed by an expressive agent at different levels of abstraction. The results provide insights on the use of such protocols for studying the effect of various models and modalities on the perception of complex emotions.

EmotionsOnto: an Ontology for Developing Affective Applications

Abstract: EmotionsOnto is a generic ontology for describing emotions and their detection and expression systems taking contextual and multimodal elements into account. The ontology is proposed as a way to develop an easily computerizable and flexible formal model. Moreover, it is based on the Web Ontology Language (OWL) standard, which also makes ontologies easily shareable and extensible. Once formalized as an ontology, the knowledge about emotions can be used in order to make computers more personalised and adapted to users' needs. The ontology has been validated and evaluated by means of an applications based on a emotionsaware Tangible User Interface (TUI). The TUI is guided by emotion knowledge previously gathered using the same TUI and modelled using EmotionsOnto

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

More than a decade has passed since research on automatic recognition of emotion from speech has become a new field of research in line with its 'big brothers' speech and speaker recognition. This article attempts to provide a short overview on where we are today, how we got there and what this can reveal us on where to go next and how we could arrive there. In a first part, we address the basic phenomenon reflecting the last fifteen years, commenting on databases, modelling and annotation, the unit of analysis and prototypicality. We then shift to automatic processing including discussions on features, classification, robustness, evaluation, and implementation and system integration. From there we go to the first comparative challenge on emotion recognition from speech-the INTERSPEECH 2009 Emotion Challenge, organised by (part of) the authors, including the description of the Challenge's database, Sub-Challenges, participants and their approaches, the winners, and the fusion of results to the actual learnt lessons before we finally address the ever-lasting problems and future promising attempts. (C) 2011 Elsevier B.V. All rights reserved.Schuller B., Batliner A., Steidl S., Seppi D., ''Recognising realistic emotions and affect in speech: state of the art and lessons learnt from the first challenge'', Speech communication, vol. 53, no. 9-10, pp. 1062-1087, November 2011.status: publishe

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference