{"title":"Speech Emotion Recognition Using Machine Learning","authors":"Aman Kumar, Vishrut Kumar, P. Rajakumar","doi":"10.1109/ICIPTM57143.2023.10118251","DOIUrl":null,"url":null,"abstract":"In the field of human-computer interaction, identifying the emotions conveyed in a person's speech is a challenge that is both incredibly fascinating and challenging. Recent times have seen a significant uptick in people's interest in this topic. In the subject of speech emotion recognition, a wide variety of techniques have been applied in order to extract emotions from signals. These techniques include a number of well-known speech analysis and classification strategies. This paper provides an overview of the deep learning technique, which is based on a simple algorithm based on feature extraction and model creation that recognizes emotion. In the traditional method of speech emotion recognition, features are first extracted from the speech signals, then the features themselves are picked, collectively known as the selection module, and then the emotions are recognized.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIPTM57143.2023.10118251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of human-computer interaction, identifying the emotions conveyed in a person's speech is a challenge that is both incredibly fascinating and challenging. Recent times have seen a significant uptick in people's interest in this topic. In the subject of speech emotion recognition, a wide variety of techniques have been applied in order to extract emotions from signals. These techniques include a number of well-known speech analysis and classification strategies. This paper provides an overview of the deep learning technique, which is based on a simple algorithm based on feature extraction and model creation that recognizes emotion. In the traditional method of speech emotion recognition, features are first extracted from the speech signals, then the features themselves are picked, collectively known as the selection module, and then the emotions are recognized.