{"title":"自动转录钢琴复调音乐","authors":"A. Kobzantsev, D. Chazan, Y. Zeevi","doi":"10.1109/ISPA.2005.195447","DOIUrl":null,"url":null,"abstract":"A novel algorithm for automatic transcription of piano polyphonic music is proposed. It is based on a processing scheme that incorporates the following subtasks: segmentation of notes in time domain, estimation of frequency components based on the structure of time segments, extraction of pitches of underlying notes, and tracking of notes to obtain the final music score. A combination of multiresolution techniques, such as multiresolution Fourier transform and maximum likelihood frequency estimator, enables the user to successfully cope with the problems of constant time-frequency resolution and frequency masking. The algorithm demonstrates a better performance then results obtained by means of existing commercial software.","PeriodicalId":238993,"journal":{"name":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","volume":"201 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Automatic transcription of piano polyphonic music\",\"authors\":\"A. Kobzantsev, D. Chazan, Y. Zeevi\",\"doi\":\"10.1109/ISPA.2005.195447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel algorithm for automatic transcription of piano polyphonic music is proposed. It is based on a processing scheme that incorporates the following subtasks: segmentation of notes in time domain, estimation of frequency components based on the structure of time segments, extraction of pitches of underlying notes, and tracking of notes to obtain the final music score. A combination of multiresolution techniques, such as multiresolution Fourier transform and maximum likelihood frequency estimator, enables the user to successfully cope with the problems of constant time-frequency resolution and frequency masking. The algorithm demonstrates a better performance then results obtained by means of existing commercial software.\",\"PeriodicalId\":238993,\"journal\":{\"name\":\"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.\",\"volume\":\"201 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2005.195447\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2005.195447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel algorithm for automatic transcription of piano polyphonic music is proposed. It is based on a processing scheme that incorporates the following subtasks: segmentation of notes in time domain, estimation of frequency components based on the structure of time segments, extraction of pitches of underlying notes, and tracking of notes to obtain the final music score. A combination of multiresolution techniques, such as multiresolution Fourier transform and maximum likelihood frequency estimator, enables the user to successfully cope with the problems of constant time-frequency resolution and frequency masking. The algorithm demonstrates a better performance then results obtained by means of existing commercial software.