Amrith Krishna, P. V. Rajkumar, K. P. Saishankar, M. John
{"title":"利用隐马尔可夫模型识别卡纳蒂克拉格","authors":"Amrith Krishna, P. V. Rajkumar, K. P. Saishankar, M. John","doi":"10.1109/SAMI.2011.5738857","DOIUrl":null,"url":null,"abstract":"Raaga identification is one of the key areas for budding Carnatic musicians and avid listeners. Identification and knowledge of the raaga of a song not only implies knowledge of music but also helps establish the mood of a song. We propose to identify a Carnatic raaga by extracting from the music sample, information about the 12 distinguishable frequencies in an octave. The proposed technique is Specmurt analysis which involves the analysis of a signal in its log-frequency domain. The extracted information is fed to the Hidden Markov Model back-end system where each raaga has its associated model.","PeriodicalId":202398,"journal":{"name":"2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"2429 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Identification of Carnatic raagas using Hidden Markov Models\",\"authors\":\"Amrith Krishna, P. V. Rajkumar, K. P. Saishankar, M. John\",\"doi\":\"10.1109/SAMI.2011.5738857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Raaga identification is one of the key areas for budding Carnatic musicians and avid listeners. Identification and knowledge of the raaga of a song not only implies knowledge of music but also helps establish the mood of a song. We propose to identify a Carnatic raaga by extracting from the music sample, information about the 12 distinguishable frequencies in an octave. The proposed technique is Specmurt analysis which involves the analysis of a signal in its log-frequency domain. The extracted information is fed to the Hidden Markov Model back-end system where each raaga has its associated model.\",\"PeriodicalId\":202398,\"journal\":{\"name\":\"2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"2429 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2011.5738857\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2011.5738857","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Carnatic raagas using Hidden Markov Models
Raaga identification is one of the key areas for budding Carnatic musicians and avid listeners. Identification and knowledge of the raaga of a song not only implies knowledge of music but also helps establish the mood of a song. We propose to identify a Carnatic raaga by extracting from the music sample, information about the 12 distinguishable frequencies in an octave. The proposed technique is Specmurt analysis which involves the analysis of a signal in its log-frequency domain. The extracted information is fed to the Hidden Markov Model back-end system where each raaga has its associated model.