Leila Kerkeni, Y. Serrestou, M. Mbarki, K. Raoof, M. Mahjoub
{"title":"A review on speech emotion recognition: Case of pedagogical interaction in classroom","authors":"Leila Kerkeni, Y. Serrestou, M. Mbarki, K. Raoof, M. Mahjoub","doi":"10.1109/ATSIP.2017.8075575","DOIUrl":null,"url":null,"abstract":"Emotions play a key role in cognitive processes, particularly in learning. Educators should know the emotional state of each student during a teaching activity. They must help students to experiment, interact and explore new topics and constructs. Students must feel in a state that maximize their performance. To know the emotional state of student, we need an emotion recognition system. It can be based on emotion recognition from speech (SER). SER is an important research area in humancomputer systems interaction (HCI). The major challenges for making a speech emotion recognition system are selecting the most suitable features and choosing the appropriate classification method. In this paper, we overview emotional speech recognition bearing in mind the role of emotions in learning. Here below we present briefly the obtained results by our SER system.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP.2017.8075575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
Emotions play a key role in cognitive processes, particularly in learning. Educators should know the emotional state of each student during a teaching activity. They must help students to experiment, interact and explore new topics and constructs. Students must feel in a state that maximize their performance. To know the emotional state of student, we need an emotion recognition system. It can be based on emotion recognition from speech (SER). SER is an important research area in humancomputer systems interaction (HCI). The major challenges for making a speech emotion recognition system are selecting the most suitable features and choosing the appropriate classification method. In this paper, we overview emotional speech recognition bearing in mind the role of emotions in learning. Here below we present briefly the obtained results by our SER system.