{"title":"情绪警报:语音邮件信息中基于hmm的情绪检测","authors":"Zeynep Inanoglu, R. Caneel","doi":"10.1145/1040830.1040885","DOIUrl":null,"url":null,"abstract":"Voicemail has become an integral part of our personal and professional communication. The number of messages that accumulate in our voice mailboxes necessitate new ways of prioritizing them. Currently, we are forced to actively listen to all messages in order to find out which ones are important and which ones can be attended to later on. In this paper, we describe Emotive Alert, a system that can detect some of the significant emotions in a new message and notify the account owner along various affective axes, including urgency, formality, valence (happy vs. sad) and arousal (calm vs. excited). We have used a purely acoustic, HMM-based approach for identifying the emotions, which allows application of this system to all messages independent of language.","PeriodicalId":376409,"journal":{"name":"Proceedings of the 10th international conference on Intelligent user interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":"{\"title\":\"Emotive alert: HMM-based emotion detection in voicemail messages\",\"authors\":\"Zeynep Inanoglu, R. Caneel\",\"doi\":\"10.1145/1040830.1040885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Voicemail has become an integral part of our personal and professional communication. The number of messages that accumulate in our voice mailboxes necessitate new ways of prioritizing them. Currently, we are forced to actively listen to all messages in order to find out which ones are important and which ones can be attended to later on. In this paper, we describe Emotive Alert, a system that can detect some of the significant emotions in a new message and notify the account owner along various affective axes, including urgency, formality, valence (happy vs. sad) and arousal (calm vs. excited). We have used a purely acoustic, HMM-based approach for identifying the emotions, which allows application of this system to all messages independent of language.\",\"PeriodicalId\":376409,\"journal\":{\"name\":\"Proceedings of the 10th international conference on Intelligent user interfaces\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th international conference on Intelligent user interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1040830.1040885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th international conference on Intelligent user interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1040830.1040885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emotive alert: HMM-based emotion detection in voicemail messages
Voicemail has become an integral part of our personal and professional communication. The number of messages that accumulate in our voice mailboxes necessitate new ways of prioritizing them. Currently, we are forced to actively listen to all messages in order to find out which ones are important and which ones can be attended to later on. In this paper, we describe Emotive Alert, a system that can detect some of the significant emotions in a new message and notify the account owner along various affective axes, including urgency, formality, valence (happy vs. sad) and arousal (calm vs. excited). We have used a purely acoustic, HMM-based approach for identifying the emotions, which allows application of this system to all messages independent of language.