2015 International Conference on Affective Computing and Intelligent Interaction (ACII)最新文献_第6页

Perception of congruent facial and kinesthetic expressions of emotions 知觉一致的面部和动觉的情绪表达

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344697

Yoren Gaffary, Jean-Claude Martin, M. Ammi

引用次数: 2

Cross-language acoustic emotion recognition: An overview and some tendencies 跨语言声音情感识别:综述及趋势

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344561

S. M. Feraru, Dagmar M. Schuller, Björn Schuller

{"title":"Cross-language acoustic emotion recognition: An overview and some tendencies","authors":"S. M. Feraru, Dagmar M. Schuller, Björn Schuller","doi":"10.1109/ACII.2015.7344561","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344561","url":null,"abstract":"Automatic emotion recognition from speech has matured close to the point where it reaches broader commercial interest. One of the last major limiting factors is the ability to deal with multilingual inputs as will be given in a real-life operating system in many if not most cases. As in real-life scenarios speech is often used mixed across languages more experience will be needed in performance effects of cross-language recognition. In this contribution we first provide an overview on languages covered in the research on emotion and speech finding that only roughly two thirds of native speakers' languages are so far touched upon. We thus next shed light on mis-matched vs matched condition emotion recognition across a variety of languages. By intention, we include less researched languages of more distant language families such as Burmese, Romanian or Turkish. Binary arousal and valence mapping is employed in order to be able to train and test across databases that have originally been labelled in diverse categories. In the result - as one may expect - arousal recognition works considerably better across languages than valence, and cross-language recognition falls considerably behind within-language recognition. However, within-language family recognition seems to provide an `emergency-solution' in case of missing language resources, and the observed notable differences depending on the combination of languages show a number of interesting effects.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"17 1","pages":"125-131"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84557224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 58

Pain level recognition using kinematics and muscle activity for physical rehabilitation in chronic pain 利用运动学和肌肉活动识别慢性疼痛的疼痛水平

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344578

Temitayo A. Olugbade, N. Bianchi-Berthouze, Nicolai Marquardt, A. Williams

{"title":"Pain level recognition using kinematics and muscle activity for physical rehabilitation in chronic pain","authors":"Temitayo A. Olugbade, N. Bianchi-Berthouze, Nicolai Marquardt, A. Williams","doi":"10.1109/ACII.2015.7344578","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344578","url":null,"abstract":"People with chronic musculoskeletal pain would benefit from technology that provides run-time personalized feedback and help adjust their physical exercise plan. However, increased pain during physical exercise, or anxiety about anticipated pain increase, may lead to setback and intensified sensitivity to pain. Our study investigates the possibility of detecting pain levels from the quality of body movement during two functional physical exercises. By analyzing recordings of kinematics and muscle activity, our feature optimization algorithms and machine learning techniques can automatically discriminate between people with low level pain and high level pain and control participants while exercising. Best results were obtained from feature set optimization algorithms: 94% and 80% for the full trunk flexion and sit-to-stand movements respectively using Support Vector Machines. As depression can affect pain experience, we included participants' depression scores on a standard questionnaire and this improved discrimination between the control participants and the people with pain when Random Forests were used.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"8 1","pages":"243-249"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79952632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 49

Real-time robust recognition of speakers' emotions and characteristics on mobile platforms 在移动平台上实时鲁棒识别说话人的情绪和特征

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344658

F. Eyben, Bernd Huber, E. Marchi, Dagmar M. Schuller, Björn Schuller

引用次数: 15

Affective handshake with a humanoid robot: How do participants perceive and combine its facial and haptic expressions? 与人形机器人的情感握手:参与者如何感知并结合其面部和触觉表情?

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344592

Mohamed Yacine Tsalamlal, Jean-Claude Martin, M. Ammi, A. Tapus, M. Amorim

引用次数: 17

Towards incorporating affective feedback into context-aware intelligent environments 将情感反馈整合到上下文感知的智能环境中

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344550

D. Saha, Thomas L. Martin, R. Benjamin Knapp

引用次数: 10

Modeling head motion entrainment for prediction of couples' behavioral characteristics 基于头部运动夹带的情侣行为特征预测模型

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344556

Bo Xiao, P. Georgiou, Brian R. Baucom, Shrikanth S. Narayanan

引用次数: 5

Relevant body cues for the classification of emotional body expression in daily actions 日常行为中情绪身体表达分类的相关身体线索

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344582

Nesrine Fourati, C. Pelachaud

引用次数: 12

Automatic assessment and analysis of public speaking anxiety: A virtual audience case study 公共演讲焦虑的自动评估与分析:一个虚拟听众案例研究

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344570

T. Wörtwein, Louis-Philippe Morency, Stefan Scherer

{"title":"Automatic assessment and analysis of public speaking anxiety: A virtual audience case study","authors":"T. Wörtwein, Louis-Philippe Morency, Stefan Scherer","doi":"10.1109/ACII.2015.7344570","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344570","url":null,"abstract":"Public speaking has become an integral part of many professions and is central to career building opportunities. Yet, public speaking anxiety is often referred to as the most common fear in everyday life and can hinder one's ability to speak in public severely. While virtual and real audiences have been successfully utilized to treat public speaking anxiety in the past, little work has been done on identifying behavioral characteristics of speakers suffering from anxiety. In this work, we focus on the characterization of behavioral indicators and the automatic assessment of public speaking anxiety. We identify several indicators for public speaking anxiety, among them are less eye contact with the audience, reduced variability in the voice, and more pauses. We automatically assess the public speaking anxiety as reported by the speakers through a self-assessment questionnaire using a speaker independent paradigm. Our approach using ensemble trees achieves a high correlation between ground truth and our estimation (r=0.825). Complementary to automatic measures of anxiety, we are also interested in speakers' perceptual differences when interacting with a virtual audience based on their level of anxiety in order to improve and further the development of virtual audiences for the training of public speaking and the reduction of anxiety.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"77 1","pages":"187-193"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74804240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30

Engagement detection based on mutli-party cues for human robot interaction 基于多方线索的人机交互交战检测

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344593

Hanan Salam, M. Chetouani

{"title":"Engagement detection based on mutli-party cues for human robot interaction","authors":"Hanan Salam, M. Chetouani","doi":"10.1109/ACII.2015.7344593","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344593","url":null,"abstract":"In this paper, we address the problematic of automatic detection of engagement in multi-party Human-Robot Interaction scenarios. The aim is to investigate to what extent are we able to infer the engagement of one of the entities of a group based solely on the cues of the other entities present in the interaction. In a scenario featuring 3 entities: 2 participants and a robot, we extract behavioural cues that concern each of the entities, we then build models based solely on each of these entities' cues and on combinations of them to predict the engagement level of each of the participants. Person-level cross validation shows that we are capable of detecting the engagement of the participant in question using solely the behavioural cues of the robot with a high accuracy compared to using the participant's cues himself (75.91% vs. 74.32%). Moreover using the behavioural cues of the other participant is also informative where it permits the detection of the engagement of the participant in question at an accuracy of 62.15% on average. The correlation between the features of the other participant with the engagement labels of the participant in question suggests a high cohesion between the two participants. In addition, the similarity of the most significantly correlated features among the two participants suggests a high synchrony between the two parties.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"71 1","pages":"341-347"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76772461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24