{"title":"语音信号的四阶累积量用于基音估计","authors":"H. Maalem, F. Marir","doi":"10.1109/ICIT.2004.1490749","DOIUrl":null,"url":null,"abstract":"In a number of speech applications, such as coding, synthesis or recognition, it is crucial to make a reliable discrimination between voiced/unvoiced segments and accurately determine the pitch period. The problem of an accurate estimation and decision in noisy condition remains open higher-order statistics (H.O.S) have inherent properties that make them well suited when dealing with a mixture of Gaussian and non-Gaussian processes. This paper explores the fourth order cumulant using autoregressive (AR(p)) and presents a new algorithm for pitch detection of voiced sounds with and without colored Gaussian noise and shows the superiority of the novel method over the classical methods such as cepstral method.","PeriodicalId":136064,"journal":{"name":"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The fourth order cumulant of speech signals applied to pitch estimation\",\"authors\":\"H. Maalem, F. Marir\",\"doi\":\"10.1109/ICIT.2004.1490749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a number of speech applications, such as coding, synthesis or recognition, it is crucial to make a reliable discrimination between voiced/unvoiced segments and accurately determine the pitch period. The problem of an accurate estimation and decision in noisy condition remains open higher-order statistics (H.O.S) have inherent properties that make them well suited when dealing with a mixture of Gaussian and non-Gaussian processes. This paper explores the fourth order cumulant using autoregressive (AR(p)) and presents a new algorithm for pitch detection of voiced sounds with and without colored Gaussian noise and shows the superiority of the novel method over the classical methods such as cepstral method.\",\"PeriodicalId\":136064,\"journal\":{\"name\":\"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2004.1490749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2004.1490749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The fourth order cumulant of speech signals applied to pitch estimation
In a number of speech applications, such as coding, synthesis or recognition, it is crucial to make a reliable discrimination between voiced/unvoiced segments and accurately determine the pitch period. The problem of an accurate estimation and decision in noisy condition remains open higher-order statistics (H.O.S) have inherent properties that make them well suited when dealing with a mixture of Gaussian and non-Gaussian processes. This paper explores the fourth order cumulant using autoregressive (AR(p)) and presents a new algorithm for pitch detection of voiced sounds with and without colored Gaussian noise and shows the superiority of the novel method over the classical methods such as cepstral method.