{"title":"音频模式搜索和检索","authors":"R. Gubka, M. Kuba","doi":"10.1109/RADIOELEK.2011.5936407","DOIUrl":null,"url":null,"abstract":"Pattern searching and retrieval plays important role in task of content-based audio analysis for requirements of media database management or in surveillance systems for detecting significant audio events and keywords. In the paper, we present algorithm for spotting audio patterns in record, using Hidden Markov Models and Viterbi decoder. Also, two types of probability normalization are presented and compared. Performance of proposed algorithm was evaluated on database of slovak spoken numbers.","PeriodicalId":267447,"journal":{"name":"Proceedings of 21st International Conference Radioelektronika 2011","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Audio patterns searching and retrieval\",\"authors\":\"R. Gubka, M. Kuba\",\"doi\":\"10.1109/RADIOELEK.2011.5936407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pattern searching and retrieval plays important role in task of content-based audio analysis for requirements of media database management or in surveillance systems for detecting significant audio events and keywords. In the paper, we present algorithm for spotting audio patterns in record, using Hidden Markov Models and Viterbi decoder. Also, two types of probability normalization are presented and compared. Performance of proposed algorithm was evaluated on database of slovak spoken numbers.\",\"PeriodicalId\":267447,\"journal\":{\"name\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADIOELEK.2011.5936407\",\"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 21st International Conference Radioelektronika 2011","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADIOELEK.2011.5936407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern searching and retrieval plays important role in task of content-based audio analysis for requirements of media database management or in surveillance systems for detecting significant audio events and keywords. In the paper, we present algorithm for spotting audio patterns in record, using Hidden Markov Models and Viterbi decoder. Also, two types of probability normalization are presented and compared. Performance of proposed algorithm was evaluated on database of slovak spoken numbers.
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