2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)最新文献_第4页

Multi-Scale Convolutional Recurrent Neural Network with Ensemble Method for Weakly Labeled Sound Event Detection 基于集成方法的多尺度卷积递归神经网络弱标记声事件检测

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925176

Yingmei Guo, Mingxing Xu, Zhiyong Wu, Jianming Wu, Bin Su

引用次数: 16

Comfortability Detection for Adaptive Human-Robot Interactions 自适应人机交互的舒适性检测

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925017

Maria Elena Lechuga Redondo

引用次数: 4

Vicarious Value Learning and Inference in Human-Human and Human-Robot Interaction 人机交互中的替代价值学习与推理

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925235

Robert J. Lowe, A. Almer, P. Gander, C. Balkenius

{"title":"Vicarious Value Learning and Inference in Human-Human and Human-Robot Interaction","authors":"Robert J. Lowe, A. Almer, P. Gander, C. Balkenius","doi":"10.1109/ACIIW.2019.8925235","DOIUrl":"https://doi.org/10.1109/ACIIW.2019.8925235","url":null,"abstract":"Among the biggest challenges for researchers of human-robot interaction is imbuing robots with lifelong learning capacities that allow efficient interactions between humans and robots. In order to address this challenge we are developing computational mechanisms for a humanoid robotic agent utilizing both system 1 and system 2-like cognitive processing capabilities. At the core of this processing is a Social Affective Appraisal model that allows for vicarious value learning and inference. Using a multi-dimensional reinforcement learning approach the robotic agent learns affective value-based functions (system 1). This learning can ground representations of affective relations (predicates) relevant to interacting agents. In this article we discuss the existing theoretical basis for developing our neural network model as a system 1-like process. We also discuss initial ideas for developing system 2-like top-down/generative affective (semantic relation-based) processing. The aim of the symbolic-connectionist architectural development is to promote autonomous capabilities in humanoid robots for interacting efficiently/intelligently (recombinant application of learned associations) with humans in changing and challenging environments.","PeriodicalId":193568,"journal":{"name":"2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116382588","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: 7

Facial Expression Recognition with Identity and Spatial-temporal Integrated Learning 身份识别与时空整合学习的面部表情识别

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925212

Jianing Teng, Dong Zhang, Ming Li, Yudong Huang

引用次数: 3

Multi-Timescale Sensitive Movement Technologies: the EnTimeMent project 多时间尺度敏感运动技术:entiment项目

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925207

A. Camurri

引用次数: 0

Deliberative and Affective Reasoning: a Bayesian Dual-Process Model 审慎和情感推理:贝叶斯双过程模型

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925215

J. Hoey, Z. Sheikhbahaee, N. MacKinnon

{"title":"Deliberative and Affective Reasoning: a Bayesian Dual-Process Model","authors":"J. Hoey, Z. Sheikhbahaee, N. MacKinnon","doi":"10.1109/ACIIW.2019.8925215","DOIUrl":"https://doi.org/10.1109/ACIIW.2019.8925215","url":null,"abstract":"The presence of artificial agents in human social networks is growing. From chatbots to robots, human experience in the developed world is moving towards a socio-technical system in which agents can be technological or biological, with increasingly blurred distinctions between. Given that emotion is a key element of human interaction, enabling artificial agents with the ability to reason about affect is a key stepping stone towards a future in which technological agents and humans can work together. This paper presents work on building intelligent computational agents that integrate both emotion and cognition. These agents are grounded in the well-established social-psychological Bayesian Affect Control Theory (BayesAct). The core idea of BayesAct is that humans are motivated in their social interactions by affective alignment: they strive for their social experiences to be coherent at a deep, emotional level with their sense of identity and general world views as constructed through culturally shared symbols. This affective alignment creates cohesive bonds between group members, and is instrumental for collaborations to solidify as relational group commitments. BayesAct agents are motivated in their social interactions by a combination of affective alignment and decision theoretic reasoning, trading the two off as a function of the uncertainty or unpredictability of the situation. This paper provides a high-level view of dual process theories and advances BayesAct as a plausible, computationally tractable model based in social-psychological and sociological theory.","PeriodicalId":193568,"journal":{"name":"2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134446988","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: 0

An Effectiveness Comparison between the Use of Activity State Data and That of Activity Magnitude Data in Chronic Stress Recognition 活动状态数据与活动强度数据在慢性应激识别中的有效性比较

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925222

Yoshiki Nakashima, Terumi Umematsu, M. Tsujikawa, Yoshifumi Onishi

{"title":"An Effectiveness Comparison between the Use of Activity State Data and That of Activity Magnitude Data in Chronic Stress Recognition","authors":"Yoshiki Nakashima, Terumi Umematsu, M. Tsujikawa, Yoshifumi Onishi","doi":"10.1109/ACIIW.2019.8925222","DOIUrl":"https://doi.org/10.1109/ACIIW.2019.8925222","url":null,"abstract":"Our aim is to improve the performance of the early recognition of chronic stress, through more effective monitoring of physiological signals produced as people live their daily lives (as opposed to monitoring during brief examination periods when physical activity is controlled). Physiological signals are influenced not only by responses to stress but also by physical activities, and it is necessary to distinguish between these two types of influence. There are basically two approaches to doing this. One is to separate the signals in terms of states of physical activity, such as sitting, walking, or running (the “Activity State” approach), and the other is to separate the signals in terms of the magnitude of physical activity (the “Activity Magnitude” approach). To determine which approach leads to better stress recognition performance, we performed evaluations using a database of 64 subjects and compared results for the two approaches. Results showed that the “Activity State” approach was, to a statistically significant degree, superior to the “Activity Magnitude” approach in the recognition of chronic stress.","PeriodicalId":193568,"journal":{"name":"2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133921381","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: 3

Analysis of Online Suicide Risk with Document Embeddings and Latent Dirichlet Allocation 基于文档嵌入和潜在Dirichlet分配的网络自杀风险分析

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925077

Noah Jones, Natasha Jaques, Pat Pataranutaporn, Asma Ghandeharioun, Rosalind W. Picard

引用次数: 5

I see what you did there: Understanding when to trust a ML model with NOVA 我看到了您在这里所做的:了解何时使用NOVA信任ML模型

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925214

Tobias Baur, Alexander Heimerl, F. Lingenfelser, E. André

引用次数: 0

Improving Automatic Pain Level Recognition using Pain Site as an Auxiliary Task 利用疼痛部位作为辅助任务改进自动疼痛等级识别

2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2019-09-01 DOI: 10.1109/ACIIW.2019.8925185

Hui-Ting Hong, Jeng-Lin Li, Chun-Min Chang, Chi-Chun Lee

{"title":"Improving Automatic Pain Level Recognition using Pain Site as an Auxiliary Task","authors":"Hui-Ting Hong, Jeng-Lin Li, Chun-Min Chang, Chi-Chun Lee","doi":"10.1109/ACIIW.2019.8925185","DOIUrl":"https://doi.org/10.1109/ACIIW.2019.8925185","url":null,"abstract":"Pain is an unpleasant sensory and distressing feeling usually induced by physical damages, and the intensity is further modulated by the experienced pain site. Objective assessment of pain is critical in a variety of clinical practices, however, the status quo in medical practices is based solely on self-report. Recent advancements have been observed in automatic assessment of pain using audio-video recordings, but most do not consider the complex clinical dependency between pain level and pain site. In this study, we propose a Task Specific Encoder with Soft Layer Ordering structure (TSEN-SLO) that utilizes a learnable tensor to flexibly share information between pain level and pain site while still keeping the representations of each task in their self-encoding layers to improve pain level recognition. Our network learns from both face and voice data and achieves accuracy of 70% and 48.1% in a binary and ternary self-report pain level classification in a challenging in-the-wild setting. The approach improves a relative of 6.5% and 9.1% compare to previous work on the same dataset. Further analysis also demonstrates the variation in the self-reported pain level as observed in the facial and acoustic features for different pain sites, which points toward a potential relationship between the neural-mechanism behind internal pain sensation and its effect on expressive facial/vocal behaviors.","PeriodicalId":193568,"journal":{"name":"2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127517767","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: 1