{"title":"建模强度轮廓和音调和强度的相互作用,以提高自动韵律事件检测和分类","authors":"A. Rosenberg","doi":"10.1109/SLT.2012.6424253","DOIUrl":null,"url":null,"abstract":"Prosody, or the way words are spoken, carries important information to understanding a speaker's communicative intention. Many studies on automatic prosodic analysis focus on parameterizing pitch content. In this work, we extend previous pitch contour modeling features to intensity contours, and develop a set of features based on the interaction of pitch and intensity. These new features improve the state-of-the-art on all prosodic event detection and classification tasks related to automatic ToBI labeling.","PeriodicalId":375378,"journal":{"name":"2012 IEEE Spoken Language Technology Workshop (SLT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Modeling intensity contours and the interaction of pitch and intensity to improve automatic prosodic event detection and classification\",\"authors\":\"A. Rosenberg\",\"doi\":\"10.1109/SLT.2012.6424253\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prosody, or the way words are spoken, carries important information to understanding a speaker's communicative intention. Many studies on automatic prosodic analysis focus on parameterizing pitch content. In this work, we extend previous pitch contour modeling features to intensity contours, and develop a set of features based on the interaction of pitch and intensity. These new features improve the state-of-the-art on all prosodic event detection and classification tasks related to automatic ToBI labeling.\",\"PeriodicalId\":375378,\"journal\":{\"name\":\"2012 IEEE Spoken Language Technology Workshop (SLT)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Spoken Language Technology Workshop (SLT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SLT.2012.6424253\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Spoken Language Technology Workshop (SLT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SLT.2012.6424253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling intensity contours and the interaction of pitch and intensity to improve automatic prosodic event detection and classification
Prosody, or the way words are spoken, carries important information to understanding a speaker's communicative intention. Many studies on automatic prosodic analysis focus on parameterizing pitch content. In this work, we extend previous pitch contour modeling features to intensity contours, and develop a set of features based on the interaction of pitch and intensity. These new features improve the state-of-the-art on all prosodic event detection and classification tasks related to automatic ToBI labeling.