10:00   Oral Session 4-KzZ – Emotion Evaluation 1
Chair: Roddy Cowie
10:00
25 mins 		A Computational Model to Relay Emotions with Tactile Stimuli
Victor V. Kryssanov, Eric W. Cooper, Hitoshi Ogawa, Izumi Kurose
Abstract: Haptic sensations have a long history of semantic relationship with various cognitive states and communication experiences. In developing multimedia interfaces, engineers would benefit greatly from knowing how sense of touch relates to human emotions. An important step in understanding this relationship is to study possible links between linguistic representations of the major haptic and emotional groups. This paper describes an attempt to reveal the semantic associations between basic categories of emotion and primary haptic sensations apparently existing in a culturally homogeneous group. A computational model is proposed to relay emotional experiences assessed on scales of “pleasure-unpleasure” and ”anxiety-boredom” with a standard haptic display, such as PHANToM. The model is defined in basic terms of physics, and can be used in virtually any application supporting haptic environments.
10:25
25 mins 		Fundamental issues on the recognition of autonomic patterns produced by visual stimuli
Simone Tognetti, Cristiano Alessandro, Andrea Bonarini, Matteo Matteucci
Abstract: One of the common approaches to the automatic emotion recognition problem is based on biological signal analysis. In this context, this paper aims at identifying the biological component related to levels of arousal of the subjects, and to use such a component to automatically discriminate among these levels. We have formalized the automatic emotion recognition as a classification problem. In order to allow the system to generalize over different subjects, we addressed two crucial aspects of the procedure: normalization and cross-validation. Assuming that different subjects could react differently to the same stimuli, we defined a distance metric between their models. We performed an experiment where 14 volunteers were stimulated by means of the IAPS set of pictures divided into classes of increasing arousal intensity. Under the effect of these external visual stimuli, subjects exhibited a principal component in their autonomic space that accounts for full class separability. As a result, we observed that some of the subjects' data can be represented by the same model, while others have to be represented differently possibly due to a poor induction mechanism. This work demonstrates the possibility to build a model able to generalize over different subjects without over-fitting, but we have to guarantee that data used to build the model represent sufficiently well the measured phenomena.
10:50
25 mins 		Categorizing Terms’ Subjectivity and Polarity Manually for Opinion Mining in Chinese
Xiaoying Xu, Ya Li, Liping Hu, Jianhua Tao
Abstract: The paper proposes three principles and a clear guideline to create a large-scale Chinese sentiment lexicon for opinion mining systems. The comparative analysis between the criterions used in ready-made resource and the Subjectivity and Polarity in opinion mining system is also discussed in the paper. With the analysis results, we manually categorize 116533 entries of Hownet terms for the lexicon according to the guideline. Two experiments are conducted to investigate the reliability of manual subjectivity labeling of the terms. The result of the first experiment shows significant high agreement between different annotators, while the second experiment demonstrates the effectiveness of our lexicon in judging the polarity of subjective sentence considering the simple recognition method and verifying our approach’s high reliability.