P. D. Silva, A. Madurapperuma, A. Marasinghe, M. Osano
{"title":"将动画教学主体作为激励支持者融入互动系统","authors":"P. D. Silva, A. Madurapperuma, A. Marasinghe, M. Osano","doi":"10.1109/CRV.2006.43","DOIUrl":null,"url":null,"abstract":"In modern world, children are interested in interacting with computers in many ways, for e.g. game playing, ELearning, chatting etc. This interest could be effectively exploited to develop their personality by creating interactive systems that adapt to different emotional states and intensities of children interacting with them. Many of the existing games are designed to beat the children rather than encourage them to win. Further, many of these systems do not take neither the emotional state nor the intensity of emotions into consideration. In this paper we present an interactive multi-agent based system that recognizes child’s emotion. A social agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses an adaptation model based on the intensity of child’s emotion to change the game status. An animated pedagogical agent gives motivational help to encourage the adaptation of the system in an interactive manner. Results show that affective gesture recognition model recognizes a child’s emotion with a considerably higher rate of over 82.5% and the social agent (estimate intensity of emotion) has strong relationship with observers’ feedback except in low intensity levels.","PeriodicalId":369170,"journal":{"name":"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Integrating Animated Pedagogical Agent as Motivational Supporter into Interactive System\",\"authors\":\"P. D. Silva, A. Madurapperuma, A. Marasinghe, M. Osano\",\"doi\":\"10.1109/CRV.2006.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In modern world, children are interested in interacting with computers in many ways, for e.g. game playing, ELearning, chatting etc. This interest could be effectively exploited to develop their personality by creating interactive systems that adapt to different emotional states and intensities of children interacting with them. Many of the existing games are designed to beat the children rather than encourage them to win. Further, many of these systems do not take neither the emotional state nor the intensity of emotions into consideration. In this paper we present an interactive multi-agent based system that recognizes child’s emotion. A social agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses an adaptation model based on the intensity of child’s emotion to change the game status. An animated pedagogical agent gives motivational help to encourage the adaptation of the system in an interactive manner. Results show that affective gesture recognition model recognizes a child’s emotion with a considerably higher rate of over 82.5% and the social agent (estimate intensity of emotion) has strong relationship with observers’ feedback except in low intensity levels.\",\"PeriodicalId\":369170,\"journal\":{\"name\":\"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2006.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2006.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integrating Animated Pedagogical Agent as Motivational Supporter into Interactive System
In modern world, children are interested in interacting with computers in many ways, for e.g. game playing, ELearning, chatting etc. This interest could be effectively exploited to develop their personality by creating interactive systems that adapt to different emotional states and intensities of children interacting with them. Many of the existing games are designed to beat the children rather than encourage them to win. Further, many of these systems do not take neither the emotional state nor the intensity of emotions into consideration. In this paper we present an interactive multi-agent based system that recognizes child’s emotion. A social agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses cognitive and non-cognitive factors to estimate a child’s intensity of emotions in real time and an autonomous/intelligent agent uses an adaptation model based on the intensity of child’s emotion to change the game status. An animated pedagogical agent gives motivational help to encourage the adaptation of the system in an interactive manner. Results show that affective gesture recognition model recognizes a child’s emotion with a considerably higher rate of over 82.5% and the social agent (estimate intensity of emotion) has strong relationship with observers’ feedback except in low intensity levels.