{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1360004238944856448.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.23919/apsipa.2018.8659577"}},{"identifier":{"@type":"URI","@value":"http://xplorestaging.ieee.org/ielx7/8648538/8659446/08659577.pdf?arnumber=8659577"}},{"identifier":{"@type":"DOI","@value":"10.48550/arxiv.1808.08056"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@value":"Independent Low-Rank Matrix Analysis Based on Time-Variant Sub-Gaussian Source Model"}],"description":[{"notation":[{"@value":"Independent low-rank matrix analysis (ILRMA) is a fast and stable method for blind audio source separation. Conventional ILRMAs assume time-variant (super-)Gaussian source models, which can only represent signals that follow a super-Gaussian distribution. In this paper, we focus on ILRMA based on a generalized Gaussian distribution (GGD-ILRMA) and propose a new type of GGD-ILRMA that adopts a time-variant sub-Gaussian distribution for the source model. By using a new update scheme called generalized iterative projection for homogeneous source models, we obtain a convergence-guaranteed update rule for demixing spatial parameters. In the experimental evaluation, we show the versatility of the proposed method, i.e., the proposed time-variant sub-Gaussian source model can be applied to various types of source signal."}]},{"notation":[{"@value":"8 pages, 5 figures, To appear in the Proceedings of APSIPA ASC 2018"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1380004238944856449","@type":"Researcher","foaf:name":[{"@value":"Shinichi Mogami"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856453","@type":"Researcher","foaf:name":[{"@value":"Norihiro Takamune"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856456","@type":"Researcher","foaf:name":[{"@value":"Daichi Kitamura"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856450","@type":"Researcher","foaf:name":[{"@value":"Hiroshi Saruwatari"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856451","@type":"Researcher","foaf:name":[{"@value":"Yu Takahashi"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856578","@type":"Researcher","foaf:name":[{"@value":"Kazunobu Kondo"}]},{"@id":"https://cir.nii.ac.jp/crid/1380004238944856577","@type":"Researcher","foaf:name":[{"@value":"Hiroaki Nakajima"}]},{"@id":"https://cir.nii.ac.jp/crid/1420845751154972928","@type":"Researcher","personIdentifier":[{"@type":"KAKEN_RESEARCHERS","@value":"80334259"},{"@type":"NRID","@value":"1000080334259"},{"@type":"NRID","@value":"9000000622070"},{"@type":"NRID","@value":"9000391811781"},{"@type":"NRID","@value":"9000391805147"},{"@type":"NRID","@value":"9000258239689"},{"@type":"NRID","@value":"9000401510092"},{"@type":"NRID","@value":"9000388994985"},{"@type":"NRID","@value":"9000307254635"},{"@type":"NRID","@value":"9000347041339"},{"@type":"NRID","@value":"9000347039111"},{"@type":"NRID","@value":"9000388997177"},{"@type":"NRID","@value":"9000378058910"},{"@type":"NRID","@value":"9000262752123"},{"@type":"NRID","@value":"9000347040444"},{"@type":"NRID","@value":"9000404260514"},{"@type":"NRID","@value":"9000388994468"},{"@type":"NRID","@value":"9000347041773"},{"@type":"NRID","@value":"9000346959401"},{"@type":"NRID","@value":"9000392823227"},{"@type":"NRID","@value":"9000402439538"},{"@type":"NRID","@value":"9000399945260"},{"@type":"NRID","@value":"9000263030392"},{"@type":"NRID","@value":"9000263033655"},{"@type":"NRID","@value":"9000391812641"},{"@type":"NRID","@value":"9000347039721"},{"@type":"NRID","@value":"9000347040528"},{"@type":"NRID","@value":"9000360589227"},{"@type":"NRID","@value":"9000404261268"},{"@type":"NRID","@value":"9000375846630"},{"@type":"NRID","@value":"9000402439974"},{"@type":"NRID","@value":"9000107364902"},{"@type":"NRID","@value":"9000241154203"},{"@type":"NRID","@value":"9000391805269"},{"@type":"NRID","@value":"9000402438785"},{"@type":"NRID","@value":"9000262342847"},{"@type":"NRID","@value":"9000411980769"},{"@type":"NRID","@value":"9000414220732"},{"@type":"NRID","@value":"9000392506951"},{"@type":"NRID","@value":"9000259820294"},{"@type":"NRID","@value":"9000259826923"},{"@type":"NRID","@value":"9000263034118"},{"@type":"NRID","@value":"9000107315378"},{"@type":"NRID","@value":"9000347040139"},{"@type":"NRID","@value":"9000272250596"},{"@type":"NRID","@value":"9000263032906"},{"@type":"NRID","@value":"9000413483467"},{"@type":"NRID","@value":"9000244005651"},{"@type":"NRID","@value":"9000391813117"},{"@type":"NRID","@value":"9000391813597"},{"@type":"NRID","@value":"9000391813592"},{"@type":"NRID","@value":"9000391988070"},{"@type":"NRID","@value":"9000258118683"},{"@type":"NRID","@value":"9000347040859"},{"@type":"NRID","@value":"9000323299803"},{"@type":"NRID","@value":"9000388997936"},{"@type":"NRID","@value":"9000388991839"},{"@type":"NRID","@value":"9000366501655"},{"@type":"NRID","@value":"9000045483761"},{"@type":"NRID","@value":"9000244006936"},{"@type":"NRID","@value":"9000388996791"},{"@type":"NRID","@value":"9000244007226"},{"@type":"NRID","@value":"9000255678741"},{"@type":"NRID","@value":"9000375890635"},{"@type":"NRID","@value":"9000391988717"},{"@type":"NRID","@value":"9000392506212"},{"@type":"NRID","@value":"9000359877112"},{"@type":"NRID","@value":"9000262342870"},{"@type":"NRID","@value":"9000383074010"},{"@type":"NRID","@value":"9000347041570"},{"@type":"NRID","@value":"9000404099224"},{"@type":"NRID","@value":"9000392823490"},{"@type":"NRID","@value":"9000402384191"},{"@type":"NRID","@value":"9000017548499"},{"@type":"NRID","@value":"9000375900350"},{"@type":"NRID","@value":"9000391812371"},{"@type":"NRID","@value":"9000411648526"},{"@type":"NRID","@value":"9000263034163"},{"@type":"RESEARCHMAP","@value":"https://researchmap.jp/onono"}],"foaf:name":[{"@value":"Nobutaka Ono"}]}],"publication":{"prism:publicationName":[{"@value":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)"}],"dc:publisher":[{"@value":"IEEE"}],"prism:publicationDate":"2018-11","prism:startingPage":"1684","prism:endingPage":"1691"},"reviewed":"false","dcterms:accessRights":"http://purl.org/coar/access_right/c_abf2","url":[{"@id":"http://xplorestaging.ieee.org/ielx7/8648538/8659446/08659577.pdf?arnumber=8659577"}],"createdAt":"2019-03-18","modifiedAt":"2020-08-23","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=Audio%20and%20Speech%20Processing%20(eess.AS)","dc:title":"Audio and Speech Processing (eess.AS)"},{"@id":"https://cir.nii.ac.jp/all?q=FOS:%20Electrical%20engineering,%20electronic%20engineering,%20information%20engineering","dc:title":"FOS: Electrical engineering, electronic engineering, information engineering"},{"@id":"https://cir.nii.ac.jp/all?q=Electrical%20Engineering%20and%20Systems%20Science%20-%20Audio%20and%20Speech%20Processing","dc:title":"Electrical Engineering and Systems Science - Audio and Speech Processing"}],"project":[{"@id":"https://cir.nii.ac.jp/crid/1040282256871808384","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"16H01735"},{"@type":"JGN","@value":"JP16H01735"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16H01735/"}],"notation":[{"@language":"ja","@value":"非同期分散チャンネルへ展開するアレイ信号処理理論の深化と実世界応用"},{"@language":"en","@value":"Deepening of Array Signal Processing Theory Expanded to Asynchronous Distributed Channels and Real-World Applications"}]}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360001114027773440","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1360002218082418176","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Multichannel Signal Separation Combining Directional Clustering and Nonnegative Matrix Factorization with Spectrogram Restoration"}]},{"@id":"https://cir.nii.ac.jp/crid/1360285711822858112","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Generalized independent low-rank matrix analysis using heavy-tailed distributions for blind source separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1360292619157226880","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Multichannel Extensions of Non-Negative Matrix Factorization With Complex-Valued Data"}]},{"@id":"https://cir.nii.ac.jp/crid/1360853567706087808","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Blind Speech Extraction Based on Rank-Constrained Spatial Covariance Matrix Estimation With Multivariate Generalized Gaussian Distribution"}]},{"@id":"https://cir.nii.ac.jp/crid/1361131420293001600","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Independent Deeply Learned Matrix Analysis for Determined Audio Source Separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1361137044097020288","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Blind source separation based on a fast-convergence algorithm combining ICA and beamforming"}]},{"@id":"https://cir.nii.ac.jp/crid/1361699994450654080","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Blind separation of convolved mixtures in the frequency domain"}]},{"@id":"https://cir.nii.ac.jp/crid/1361975845223143808","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Independent Low-Rank Matrix Analysis Based on Time-Variant Sub-Gaussian Source Model for Determined Blind Source Separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1361981468951296896","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Determined Blind Source Separation with Independent Low-Rank Matrix Analysis"}]},{"@id":"https://cir.nii.ac.jp/crid/1361981469062518656","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Audio analysis of statistically instantaneous signals with mixed Gaussian probability distributions"}]},{"@id":"https://cir.nii.ac.jp/crid/1362544419228105728","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Determined Blind Source Separation via Proximal Splitting Algorithm"}]},{"@id":"https://cir.nii.ac.jp/crid/1362544419751921664","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Learning the parts of objects by non-negative matrix factorization"}]},{"@id":"https://cir.nii.ac.jp/crid/1362825894259639040","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Independent component analysis, A new concept?"}]},{"@id":"https://cir.nii.ac.jp/crid/1362825894624610688","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Blind Source Separation Exploiting Higher-Order Frequency Dependencies"}]},{"@id":"https://cir.nii.ac.jp/crid/1362825895038653440","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A Robust and Precise Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1363107368278328064","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Determined Blind Source Separation Unifying Independent Vector Analysis and Nonnegative Matrix Factorization"}]},{"@id":"https://cir.nii.ac.jp/crid/1363388846160758400","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Independent Low-Rank Matrix Analysis Based on Multivariate Complex Exponential Power Distribution"}]},{"@id":"https://cir.nii.ac.jp/crid/1364233268875870720","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Multichannel nonnegative tensor factorization with structured constraints for user-guided audio source separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1364233270413922304","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Stable and fast update rules for independent vector analysis based on auxiliary function technique"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856448","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Acoustical sound database in real environments for sound scene understanding and hands-free speech recognition"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856457","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Independent low-rank matrix analysis based on complex Student's t-distribution for blind audio source separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856458","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Performance measurement in blind audio source separation"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856463","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Solution of permutation problem in frequency domain ICA using multivariate probability density functions"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856578","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Quantile regression via an MM algorithm"}]},{"@id":"https://cir.nii.ac.jp/crid/1370004238944856581","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"The 2011 signal separation evaluation campaign (SiSEC2011): - audio source separation -"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.23919/apsipa.2018.8659577"},{"@type":"KAKEN","@value":"PRODUCT-22244663"},{"@type":"OPENAIRE","@value":"doi_dedup___::f5cff90da652b70838f1ca752b4cef94"},{"@type":"CROSSREF","@value":"10.1109/taslp.2020.3003165_references_DOI_MddVhuwF77ZfOsAM787LDlvKGZc"},{"@type":"CROSSREF","@value":"10.1109/taslp.2019.2925450_references_DOI_MddVhuwF77ZfOsAM787LDlvKGZc"},{"@type":"CROSSREF","@value":"10.1109/taslp.2019.2959257_references_DOI_MddVhuwF77ZfOsAM787LDlvKGZc"}]}