{"title":"文本到多媒体组合系统的单词端点校正技术","authors":"K. Turkowski, B. Hamidzadeh","doi":"10.1109/TAI.2002.1180821","DOIUrl":null,"url":null,"abstract":"In concatenative Text-to-Multimedia composition systems, accurate endpoint detection of the uttered audio words, used as input into such systems, is needed to ensure optimal audio concatenation. In this paper, we outline a method of endpoint detection that takes advantage of the fact that the text of the audio word is known before endpoint detection actually takes place. From the text, the associated phonemes for an uttered audio word can be determined and used to fine tune the endpoint detection for a specific given phoneme.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Word endpoint correction techniques for a text-to-multimedia composition system\",\"authors\":\"K. Turkowski, B. Hamidzadeh\",\"doi\":\"10.1109/TAI.2002.1180821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In concatenative Text-to-Multimedia composition systems, accurate endpoint detection of the uttered audio words, used as input into such systems, is needed to ensure optimal audio concatenation. In this paper, we outline a method of endpoint detection that takes advantage of the fact that the text of the audio word is known before endpoint detection actually takes place. From the text, the associated phonemes for an uttered audio word can be determined and used to fine tune the endpoint detection for a specific given phoneme.\",\"PeriodicalId\":197064,\"journal\":{\"name\":\"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.2002.1180821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.2002.1180821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Word endpoint correction techniques for a text-to-multimedia composition system
In concatenative Text-to-Multimedia composition systems, accurate endpoint detection of the uttered audio words, used as input into such systems, is needed to ensure optimal audio concatenation. In this paper, we outline a method of endpoint detection that takes advantage of the fact that the text of the audio word is known before endpoint detection actually takes place. From the text, the associated phonemes for an uttered audio word can be determined and used to fine tune the endpoint detection for a specific given phoneme.