{"title":"用广义频谱确定音乐信号的音高","authors":"T. R. Black, Kevin D. Donohue","doi":"10.1109/SECON.2000.845433","DOIUrl":null,"url":null,"abstract":"This paper presents an algorithm for detecting and estimating pitch in acoustic audio signals using the generalized spectrum (CS). A performance evaluation of a GS-based and two classical (autocorrelation- and cepstrum-based) pitch determination algorithms was conducted on a set of wavetable-synthesized musical signals. The experiment separately evaluates the tasks of pitch detection and estimation. Pitch estimation performance is presented in terms of gross pitch errors (indicating algorithm stability) and mean-squared fine pitch error. The pitch detection performance is evaluated by a receiver operating characteristic analysis of the detection statistics. Results demonstrate that the GS-based estimator generally performs worse than the autocorrelation and cepstrum-based methods. However, the GS-based method performed consistently better for the detection problem, especially at low signal-to-noise values.","PeriodicalId":206022,"journal":{"name":"Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Pitch determination of music signals using the generalized spectrum\",\"authors\":\"T. R. Black, Kevin D. Donohue\",\"doi\":\"10.1109/SECON.2000.845433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an algorithm for detecting and estimating pitch in acoustic audio signals using the generalized spectrum (CS). A performance evaluation of a GS-based and two classical (autocorrelation- and cepstrum-based) pitch determination algorithms was conducted on a set of wavetable-synthesized musical signals. The experiment separately evaluates the tasks of pitch detection and estimation. Pitch estimation performance is presented in terms of gross pitch errors (indicating algorithm stability) and mean-squared fine pitch error. The pitch detection performance is evaluated by a receiver operating characteristic analysis of the detection statistics. Results demonstrate that the GS-based estimator generally performs worse than the autocorrelation and cepstrum-based methods. However, the GS-based method performed consistently better for the detection problem, especially at low signal-to-noise values.\",\"PeriodicalId\":206022,\"journal\":{\"name\":\"Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.2000.845433\",\"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 the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2000.845433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pitch determination of music signals using the generalized spectrum
This paper presents an algorithm for detecting and estimating pitch in acoustic audio signals using the generalized spectrum (CS). A performance evaluation of a GS-based and two classical (autocorrelation- and cepstrum-based) pitch determination algorithms was conducted on a set of wavetable-synthesized musical signals. The experiment separately evaluates the tasks of pitch detection and estimation. Pitch estimation performance is presented in terms of gross pitch errors (indicating algorithm stability) and mean-squared fine pitch error. The pitch detection performance is evaluated by a receiver operating characteristic analysis of the detection statistics. Results demonstrate that the GS-based estimator generally performs worse than the autocorrelation and cepstrum-based methods. However, the GS-based method performed consistently better for the detection problem, especially at low signal-to-noise values.