{"id":"https://openalex.org/W2991853703","doi":"https://doi.org/10.1109/ispacs.2018.8923534","title":"Multi-channel Non-negative Matrix Factorization Initialized with Full-rank and Rank-1 Spatial Correlation Matrix for Speech Recognition","display_name":"Multi-channel Non-negative Matrix Factorization Initialized with Full-rank and Rank-1 Spatial Correlation Matrix for Speech Recognition","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2991853703","doi":"https://doi.org/10.1109/ispacs.2018.8923534","mag":"2991853703"},"language":"en","primary_location":{"id":"doi:10.1109/ispacs.2018.8923534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022767796","display_name":"Yuuki Tachioka","orcid":"https://orcid.org/0009-0002-0587-2943"},"institutions":[{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]},{"id":"https://openalex.org/I4210136457","display_name":"Shibuya (Japan)","ror":"https://ror.org/03t1ztz45","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210136457"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuuki Tachioka","raw_affiliation_strings":["Denso IT Laboratory, Shibuya Cross Tower, Shibuya 2-15-1, Shibuya-ku, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Denso IT Laboratory, Shibuya Cross Tower, Shibuya 2-15-1, Shibuya-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I4210136457","https://openalex.org/I4210132650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022767796"],"corresponding_institution_ids":["https://openalex.org/I4210132650","https://openalex.org/I4210136457"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.25246967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"246","last_page":"251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.8380584716796875},{"id":"https://openalex.org/keywords/overdetermined-system","display_name":"Overdetermined system","score":0.7581362128257751},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6808773875236511},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6022443771362305},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5854615569114685},{"id":"https://openalex.org/keywords/nonnegative-matrix","display_name":"Nonnegative matrix","score":0.4953802824020386},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4875445067882538},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48718923330307007},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4855194091796875},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.4787956178188324},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47309568524360657},{"id":"https://openalex.org/keywords/eigendecomposition-of-a-matrix","display_name":"Eigendecomposition of a matrix","score":0.469133585691452},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.45655789971351624},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.43670016527175903},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4265480935573578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4046873450279236},{"id":"https://openalex.org/keywords/symmetric-matrix","display_name":"Symmetric matrix","score":0.31052839756011963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2787374258041382},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.17245420813560486},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.14595037698745728}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8380584716796875},{"id":"https://openalex.org/C81901731","wikidata":"https://www.wikidata.org/wiki/Q331348","display_name":"Overdetermined system","level":2,"score":0.7581362128257751},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6808773875236511},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6022443771362305},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5854615569114685},{"id":"https://openalex.org/C139018669","wikidata":"https://www.wikidata.org/wiki/Q6961560","display_name":"Nonnegative matrix","level":4,"score":0.4953802824020386},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4875445067882538},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48718923330307007},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4855194091796875},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.4787956178188324},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47309568524360657},{"id":"https://openalex.org/C169756996","wikidata":"https://www.wikidata.org/wiki/Q194919","display_name":"Eigendecomposition of a matrix","level":3,"score":0.469133585691452},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.45655789971351624},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.43670016527175903},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4265480935573578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4046873450279236},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.31052839756011963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2787374258041382},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.17245420813560486},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.14595037698745728},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispacs.2018.8923534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2018.8923534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1902027874","https://openalex.org/W2039844283","https://openalex.org/W2072548008","https://openalex.org/W2124149378","https://openalex.org/W2148613904","https://openalex.org/W2162646593","https://openalex.org/W2168273590","https://openalex.org/W2217477878","https://openalex.org/W2288645994","https://openalex.org/W2559260703","https://openalex.org/W2747798993"],"related_works":["https://openalex.org/W2088770317","https://openalex.org/W2166191203","https://openalex.org/W2991398534","https://openalex.org/W1956621158","https://openalex.org/W4399648768","https://openalex.org/W2165495021","https://openalex.org/W1845372869","https://openalex.org/W2091334405","https://openalex.org/W2912339400","https://openalex.org/W2361362843"],"abstract_inverted_index":{"Multi-channel":[0],"non-negative":[1],"matrix":[2,40,82,87,94],"factorization":[3,88],"(MNMF)":[4],"is":[5,53,114,123],"one":[6],"of":[7,22,48,62,74,96,112,121,127,142,147,167],"the":[8,59,77,86,119,140,145,165,168],"most":[9],"effective":[10],"blind":[11],"source":[12],"separation":[13],"techniques.":[14],"This":[15,67],"paper":[16,68],"proposes":[17],"a":[18,27,36,49,63,91,97,159],"stable":[19],"initialization":[20,33,103,170],"method":[21,104,171],"MNMF":[23,150,174],"by":[24,89],"accurately":[25],"estimating":[26],"full-rank":[28,70],"spatial":[29,38,64,98],"correlation":[30,39,65,99],"matrix.":[31,66,100],"Alternative":[32],"can":[34,105,151],"be":[35,42,106],"rank-1":[37,72,92],"to":[41,58,108,138,144,198],"obtained":[43],"as":[44],"an":[45,54,115],"outer":[46],"product":[47],"steering":[50],"vector,":[51],"which":[52],"eigenvector":[55],"that":[56,126],"corresponds":[57],"maximum":[60],"eigenvalue":[61],"compares":[69],"and":[71,175,183],"types":[73],"initialization.":[75],"On":[76],"other":[78],"hand,":[79],"independent":[80],"low-rank":[81],"analysis":[83],"(ILRMA)":[84],"accelerates":[85],"using":[90],"demixing":[93],"instead":[95],"The":[101,110],"above-mentioned":[102],"applied":[107],"ILRMA.":[109,176],"drawback":[111],"ILRMA":[113,137,180,195],"overdetermined":[116,189],"situation":[117],"where":[118],"number":[120,141,146],"observations":[122,143],"greater":[124],"than":[125,185],"sources.":[128],"In":[129],"such":[130,154],"cases,":[131,179,190],"special":[132,193],"treatments":[133],"are":[134],"necessary":[135],"for":[136,173,188],"match":[139],"sources,":[148],"whereas":[149],"deal":[152],"with":[153,192],"cases":[155],"naturally.":[156],"Experiments":[157],"on":[158],"noisy":[160],"speech":[161],"recognition":[162],"task":[163],"showed":[164],"effectiveness":[166],"proposed":[169],"both":[172],"For":[177],"determined":[178],"was":[181,196],"faster":[182],"better":[184],"MNMF,":[186],"but":[187],"even":[191],"treatments,":[194],"inferior":[197],"MNMF.":[199]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}