{"title":"实时情绪分析","authors":"A. Savva, Vasso Stylianou","doi":"10.1109/ICCECE51049.2023.10084955","DOIUrl":null,"url":null,"abstract":"This paper describes the development of a system which captures students’ facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-Time Emotional Analysis\",\"authors\":\"A. Savva, Vasso Stylianou\",\"doi\":\"10.1109/ICCECE51049.2023.10084955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the development of a system which captures students’ facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.\",\"PeriodicalId\":447131,\"journal\":{\"name\":\"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE51049.2023.10084955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE51049.2023.10084955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes the development of a system which captures students’ facial expressions during a lecture and by using machine learning methods it produces a timeline of their emotions. Examples of such emotions are: happiness, surprise, fear, neutral and sadness. This can assist an educator to identify aspects for improving a lecture, such as, at which periods of time students were confused, or, in a 3-hour lecture when a break is needed, etc.