{"id":"https://openalex.org/W2051307814","doi":"https://doi.org/10.1109/icassp.2013.6637644","title":"Convex non-negative matrix factorization for automatic music structure identification","display_name":"Convex non-negative matrix factorization for automatic music structure identification","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2051307814","doi":"https://doi.org/10.1109/icassp.2013.6637644","mag":"2051307814"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6637644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5110542743","display_name":"Oriol Nieto","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Oriol Nieto","raw_affiliation_strings":["Music and Audio Research Laboratory, New York University, USA","Music and Audio Research Lab, New York University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Music and Audio Research Laboratory, New York University, USA","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Music and Audio Research Lab, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038378205","display_name":"Tristan Jehan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146847","display_name":"North Carolina Exploring Cultural Heritage Online","ror":"https://ror.org/05g5fwv52","country_code":"US","type":"archive","lineage":["https://openalex.org/I4210146847"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tristan Jehan","raw_affiliation_strings":["Echo Nest, USA"],"affiliations":[{"raw_affiliation_string":"Echo Nest, USA","institution_ids":["https://openalex.org/I4210146847"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110542743"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":4.1795,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.94429708,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"236","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music 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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music 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/T10788","display_name":"Neuroscience and Music Perception","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11349","display_name":"Music Technology and Sound Studies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.8239371180534363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6334443688392639},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6330286264419556},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.595421314239502},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5107207298278809},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.49153932929039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4752885103225708},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.460409015417099},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44928646087646484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43521010875701904},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3942296504974365}],"concepts":[{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.8239371180534363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6334443688392639},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6330286264419556},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.595421314239502},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5107207298278809},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.49153932929039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4752885103225708},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.460409015417099},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44928646087646484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43521010875701904},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3942296504974365},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"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/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},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2013.6637644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W9205999","https://openalex.org/W170769362","https://openalex.org/W179928807","https://openalex.org/W180220758","https://openalex.org/W201103045","https://openalex.org/W591222336","https://openalex.org/W1510436408","https://openalex.org/W2032085270","https://openalex.org/W2038452924","https://openalex.org/W2081681829","https://openalex.org/W2135029798","https://openalex.org/W2143235280","https://openalex.org/W2153723155","https://openalex.org/W2168103112","https://openalex.org/W2168120888","https://openalex.org/W2168249484","https://openalex.org/W2169719929","https://openalex.org/W2293125622","https://openalex.org/W2294938120","https://openalex.org/W2296587773","https://openalex.org/W2402230369","https://openalex.org/W2406901689","https://openalex.org/W2482276862","https://openalex.org/W6600360952","https://openalex.org/W6607283467","https://openalex.org/W6607482045","https://openalex.org/W6608124329","https://openalex.org/W6617581451","https://openalex.org/W6680012447","https://openalex.org/W6697158164","https://openalex.org/W6697165675","https://openalex.org/W6697408455","https://openalex.org/W6713175915","https://openalex.org/W6713620424"],"related_works":["https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840","https://openalex.org/W2146544734"],"abstract_inverted_index":{"We":[0,42],"propose":[1],"a":[2,16,24,29,36,52,59],"novel":[3],"and":[4,62,81,97],"fast":[5],"approach":[6],"to":[7,27,104],"discover":[8],"structure":[9],"in":[10,58],"western":[11],"popular":[12],"music":[13,106],"by":[14],"using":[15],"specific":[17],"type":[18],"of":[19,38,51,74,78],"matrix":[20,68,111],"factorization":[21,112],"that":[22,31,44,99],"adds":[23],"convex":[25],"constrain":[26],"obtain":[28],"decomposition":[30],"can":[32],"be":[33],"interpreted":[34],"as":[35],"set":[37],"weighted":[39],"cluster":[40],"centroids.":[41],"show":[43,98],"these":[45],"centroids":[46],"capture":[47],"the":[48,76,79],"different":[49,86,95],"sections":[50,80],"musical":[53],"piece":[54],"(e.g.":[55],"verse,":[56],"chorus)":[57],"more":[60],"consistent":[61],"efficient":[63],"way":[64],"than":[65],"classic":[66],"non-negative":[67],"factorization.":[69],"This":[70],"technique":[71],"is":[72,101],"capable":[73],"identifying":[75],"boundaries":[77],"then":[82],"grouping":[83],"them":[84],"into":[85],"clusters.":[87],"Additionally,":[88],"we":[89],"evaluate":[90],"this":[91],"method":[92],"on":[93],"two":[94],"datasets":[96],"it":[100],"competitive":[102],"compared":[103],"other":[105,110],"segmentation":[107],"techniques,":[108],"outperforming":[109],"methods.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}