N. Bassiou, Constantine Kotropoulos, Evangelia Koliopoulou
{"title":"对称α稳定稀疏线性回归用于音乐音频去噪","authors":"N. Bassiou, Constantine Kotropoulos, Evangelia Koliopoulou","doi":"10.1109/ISPA.2013.6703771","DOIUrl":null,"url":null,"abstract":"A new musical audio denoising technique is proposed, when the noise is modeled by an α-stable distribution. The proposed technique is based on sparse linear regression with structured priors and uses Markov Chain Monte Carlo inference to estimate the clean signal model parameters and the α-stable noise model parameters. Experiments on noisy Greek folk music excerpts demonstrate better denoising for the α-stable noise assumption than the Gaussian white noise one.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Symmetric α-stable sparse linear regression for musical audio denoising\",\"authors\":\"N. Bassiou, Constantine Kotropoulos, Evangelia Koliopoulou\",\"doi\":\"10.1109/ISPA.2013.6703771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new musical audio denoising technique is proposed, when the noise is modeled by an α-stable distribution. The proposed technique is based on sparse linear regression with structured priors and uses Markov Chain Monte Carlo inference to estimate the clean signal model parameters and the α-stable noise model parameters. Experiments on noisy Greek folk music excerpts demonstrate better denoising for the α-stable noise assumption than the Gaussian white noise one.\",\"PeriodicalId\":425029,\"journal\":{\"name\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2013.6703771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Symmetric α-stable sparse linear regression for musical audio denoising
A new musical audio denoising technique is proposed, when the noise is modeled by an α-stable distribution. The proposed technique is based on sparse linear regression with structured priors and uses Markov Chain Monte Carlo inference to estimate the clean signal model parameters and the α-stable noise model parameters. Experiments on noisy Greek folk music excerpts demonstrate better denoising for the α-stable noise assumption than the Gaussian white noise one.