{"id":"https://openalex.org/W2397914692","doi":"https://doi.org/10.1109/icassp.2016.7471639","title":"Music emotion recognition with adaptive aggregation of Gaussian process regressors","display_name":"Music emotion recognition with adaptive aggregation of Gaussian process regressors","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2397914692","doi":"https://doi.org/10.1109/icassp.2016.7471639","mag":"2397914692"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7471639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5003098968","display_name":"Satoru Fukayama","orcid":"https://orcid.org/0000-0001-6506-2796"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Satoru Fukayama","raw_affiliation_strings":["Sangyo Gijutsu Sogo Kenkyujo, Chiyoda-ku, Tokyo, JP"],"affiliations":[{"raw_affiliation_string":"Sangyo Gijutsu Sogo Kenkyujo, Chiyoda-ku, Tokyo, JP","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030650456","display_name":"Masataka Goto","orcid":"https://orcid.org/0000-0003-1167-0977"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masataka Goto","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST), Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST), Japan","institution_ids":["https://openalex.org/I73613424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003098968"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7653,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.8554841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9991999864578247,"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":0.9991999864578247,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.970300018787384,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7149693965911865},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5740620493888855},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.556864857673645},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5568451285362244},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5505448579788208},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5497314929962158},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5172175168991089},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5039581656455994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4878092110157013},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.46799227595329285},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42626774311065674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3611629903316498},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16800475120544434},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13400521874427795}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149693965911865},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5740620493888855},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.556864857673645},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5568451285362244},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5505448579788208},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5497314929962158},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5172175168991089},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5039581656455994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4878092110157013},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.46799227595329285},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42626774311065674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3611629903316498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16800475120544434},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13400521874427795},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7471639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W72823879","https://openalex.org/W189934255","https://openalex.org/W207683342","https://openalex.org/W434887191","https://openalex.org/W858155270","https://openalex.org/W1525367617","https://openalex.org/W1528099392","https://openalex.org/W1983507146","https://openalex.org/W1992855217","https://openalex.org/W2011853905","https://openalex.org/W2019360207","https://openalex.org/W2082927806","https://openalex.org/W2136129419","https://openalex.org/W2144707026","https://openalex.org/W2149628368","https://openalex.org/W2185845146","https://openalex.org/W2295276533","https://openalex.org/W2296043443","https://openalex.org/W2296267742","https://openalex.org/W2341090665","https://openalex.org/W2398435538","https://openalex.org/W2399188394","https://openalex.org/W2399576812","https://openalex.org/W2399943434","https://openalex.org/W2404246330","https://openalex.org/W2916566921","https://openalex.org/W4214894679","https://openalex.org/W6603032361","https://openalex.org/W6607669515","https://openalex.org/W6608508128","https://openalex.org/W6615189317","https://openalex.org/W6623798586","https://openalex.org/W6631194016","https://openalex.org/W6686053107","https://openalex.org/W6697138395","https://openalex.org/W6697308585","https://openalex.org/W6704344484","https://openalex.org/W6712352089","https://openalex.org/W6712515212","https://openalex.org/W6712892358","https://openalex.org/W6712935731"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W2368989808"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,12,46,67,83,110],"novel":[4],"method":[5,42,84],"for":[6],"estimating":[7],"the":[8,51,63,87,101,114,122,126],"emotions":[9,102],"elicited":[10,103],"by":[11,89,104,120],"piece":[13],"of":[14,112],"music":[15],"from":[16,53],"its":[17],"acoustic":[18,30,75,94],"signals.":[19],"Previous":[20],"research":[21],"in":[22,66,125,148],"this":[23],"field":[24],"has":[25],"centered":[26],"on":[27,45],"finding":[28],"effective":[29,147],"features":[31,37],"and":[32,70],"regression":[33],"methods":[34],"to":[35,38,74],"relate":[36],"emotions.":[39],"The":[40],"state-of-the-art":[41],"is":[43,146],"based":[44],"multi-stage":[47],"regression,":[48],"which":[49],"aggregates":[50],"results":[52],"different":[54,78,139],"regressors":[55],"trained":[56],"with":[57,77,135],"training":[58,127],"data.":[59],"However,":[60],"after":[61],"training,":[62],"aggregation":[64,88,115,140,145],"happens":[65],"fixed":[68],"way":[69,111],"cannot":[71,99],"be":[72],"adapted":[73],"signals":[76],"musical":[79],"properties.":[80],"We":[81,117,133],"propose":[82],"that":[85,142],"adapts":[86],"taking":[90],"into":[91],"account":[92],"new":[93,105],"signal":[95],"inputs.":[96],"Since":[97],"we":[98,108],"know":[100],"inputs":[106],"beforehand,":[107],"need":[109],"adapting":[113],"weights.":[116],"do":[118],"so":[119],"exploiting":[121],"deviation":[123],"observed":[124],"data":[128],"using":[129],"Gaussian":[130],"process":[131],"regressions.":[132],"confirmed":[134],"an":[136],"experiment":[137],"comparing":[138],"approaches":[141],"our":[143],"adaptive":[144],"improving":[149],"recognition":[150],"accuracy.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
