Yong-Ju Lee, Sook-Hyang Lee, Jong-Jin Kim, Hyun-Ju Ko, Young-Il Kim, Sanghun Kim, Jung-Cheol Lee
{"title":"利用k-toBI系统开发了一种基于节奏标记数据库的韩文F0轮廓生成计算算法","authors":"Yong-Ju Lee, Sook-Hyang Lee, Jong-Jin Kim, Hyun-Ju Ko, Young-Il Kim, Sanghun Kim, Jung-Cheol Lee","doi":"10.21437/ICSLP.1998-34","DOIUrl":null,"url":null,"abstract":"This study describes an algorithm for the F0 contour generation system for Korean sentences and its evaluation results. 400 K-ToBI labeled utterances were used which were read by one male and one female announcers. F0 contour generation system uses two classification trees for prediction of K-ToBI labels for input text and 11 regression trees for prediction of F0 values for the labels. Evaluation results of the system showed 77.2% prediction accuracy for prediction of IP boundaries and 72.0% prediction accuracy for AP boundaries. Information of voicing and duration of the segments was not changed for F0 contour generation and its evaluation. Evaluation results showed 23.5Hz RMS error and 0.55 correlation coefficient in F0 generation experiment using labelling information from the original speech data.","PeriodicalId":117113,"journal":{"name":"5th International Conference on Spoken Language Processing (ICSLP 1998)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A computational algorithm for F0 contour generation in Korean developed with prosodically labeled databases using k-toBI system\",\"authors\":\"Yong-Ju Lee, Sook-Hyang Lee, Jong-Jin Kim, Hyun-Ju Ko, Young-Il Kim, Sanghun Kim, Jung-Cheol Lee\",\"doi\":\"10.21437/ICSLP.1998-34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study describes an algorithm for the F0 contour generation system for Korean sentences and its evaluation results. 400 K-ToBI labeled utterances were used which were read by one male and one female announcers. F0 contour generation system uses two classification trees for prediction of K-ToBI labels for input text and 11 regression trees for prediction of F0 values for the labels. Evaluation results of the system showed 77.2% prediction accuracy for prediction of IP boundaries and 72.0% prediction accuracy for AP boundaries. Information of voicing and duration of the segments was not changed for F0 contour generation and its evaluation. Evaluation results showed 23.5Hz RMS error and 0.55 correlation coefficient in F0 generation experiment using labelling information from the original speech data.\",\"PeriodicalId\":117113,\"journal\":{\"name\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21437/ICSLP.1998-34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Spoken Language Processing (ICSLP 1998)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21437/ICSLP.1998-34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A computational algorithm for F0 contour generation in Korean developed with prosodically labeled databases using k-toBI system
This study describes an algorithm for the F0 contour generation system for Korean sentences and its evaluation results. 400 K-ToBI labeled utterances were used which were read by one male and one female announcers. F0 contour generation system uses two classification trees for prediction of K-ToBI labels for input text and 11 regression trees for prediction of F0 values for the labels. Evaluation results of the system showed 77.2% prediction accuracy for prediction of IP boundaries and 72.0% prediction accuracy for AP boundaries. Information of voicing and duration of the segments was not changed for F0 contour generation and its evaluation. Evaluation results showed 23.5Hz RMS error and 0.55 correlation coefficient in F0 generation experiment using labelling information from the original speech data.