{"title":"基于层次模型的集成机器学习的普通话音高重音预测","authors":"Chongjia Ni, Wenju Liu, Bo Xu","doi":"10.1109/YCICT.2009.5382357","DOIUrl":null,"url":null,"abstract":"In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine (SVM), adaboost with CART at different experimental conditions, the hierarchical model obtains the best results, it can achieve 84.75% accuracy rate to Mandarin read speech. At the same time, we compare our proposed method with previous proposed method at the same training set and test set. There are 2.25% and 0.82% absolute accuracy rate improvements.","PeriodicalId":138803,"journal":{"name":"2009 IEEE Youth Conference on Information, Computing and Telecommunication","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Mandarin pitch accent prediction using hierarchical model based ensemble machine learning\",\"authors\":\"Chongjia Ni, Wenju Liu, Bo Xu\",\"doi\":\"10.1109/YCICT.2009.5382357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine (SVM), adaboost with CART at different experimental conditions, the hierarchical model obtains the best results, it can achieve 84.75% accuracy rate to Mandarin read speech. At the same time, we compare our proposed method with previous proposed method at the same training set and test set. There are 2.25% and 0.82% absolute accuracy rate improvements.\",\"PeriodicalId\":138803,\"journal\":{\"name\":\"2009 IEEE Youth Conference on Information, Computing and Telecommunication\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Youth Conference on Information, Computing and Telecommunication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YCICT.2009.5382357\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Youth Conference on Information, Computing and Telecommunication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2009.5382357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mandarin pitch accent prediction using hierarchical model based ensemble machine learning
In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine (SVM), adaboost with CART at different experimental conditions, the hierarchical model obtains the best results, it can achieve 84.75% accuracy rate to Mandarin read speech. At the same time, we compare our proposed method with previous proposed method at the same training set and test set. There are 2.25% and 0.82% absolute accuracy rate improvements.