{"title":"Speech Emotion Recognition Overview and Experimental Results","authors":"Eva Lieskovská, Maroš Jakubec, R. Jarina","doi":"10.1109/ICETA51985.2020.9379218","DOIUrl":null,"url":null,"abstract":"Nowadays, speech emotion recognition is a promising area of research mainly for human-computer interaction. Emotions play significant role in educational process. E-learning such as online classes or student-computer interaction setting may require monitoring of emotional state of students, due to the maintaining of quality of provided education. Thus, automatic speech emotion recognition represents a powerful tool for this purpose. The following paper provides an overview of speech emotion recognition and related works. A comparison of various forms of recurrent networks (LSTM, LSTM with peephole connections, GRU) and recognition accuracy on IEMOCAP database is also presented.","PeriodicalId":149716,"journal":{"name":"2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETA51985.2020.9379218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Nowadays, speech emotion recognition is a promising area of research mainly for human-computer interaction. Emotions play significant role in educational process. E-learning such as online classes or student-computer interaction setting may require monitoring of emotional state of students, due to the maintaining of quality of provided education. Thus, automatic speech emotion recognition represents a powerful tool for this purpose. The following paper provides an overview of speech emotion recognition and related works. A comparison of various forms of recurrent networks (LSTM, LSTM with peephole connections, GRU) and recognition accuracy on IEMOCAP database is also presented.