{"id":"https://openalex.org/W4406324678","doi":"https://doi.org/10.1177/14727978251314557","title":"Development and verification of automatic recognition system for vocal performance styles based on ResNet","display_name":"Development and verification of automatic recognition system for vocal performance styles based on ResNet","publication_year":2025,"publication_date":"2025-01-13","ids":{"openalex":"https://openalex.org/W4406324678","doi":"https://doi.org/10.1177/14727978251314557"},"language":"en","primary_location":{"id":"doi:10.1177/14727978251314557","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978251314557","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-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/A5109523449","display_name":"Xu Xiang Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Ni","raw_affiliation_strings":["Guangxi Minzu University","School of Arts, Guangxi Minzu University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Minzu University","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"School of Arts, Guangxi Minzu University, Nanning, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006730214","display_name":"Xiyang Chen","orcid":"https://orcid.org/0000-0003-0166-9681"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiyang Chen","raw_affiliation_strings":["Guangxi Minzu Normal University","School of Arts, Guangxi Minzu Normal University, Chongzuo, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Minzu Normal University","institution_ids":[]},{"raw_affiliation_string":"School of Arts, Guangxi Minzu Normal University, Chongzuo, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006730214"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6525,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76457164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"25","issue":"3","first_page":"2516","last_page":"2528"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994999766349792,"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":0.9994999766349792,"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/T13996","display_name":"Diverse Musicological Studies","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1210","display_name":"Music"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11349","display_name":"Music Technology and Sound Studies","score":0.9817000031471252,"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/computer-science","display_name":"Computer science","score":0.8025602102279663},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.6466807723045349},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6051461100578308},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5980455875396729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5839444994926453},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5493613481521606},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5096578598022461},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44671177864074707},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.43869125843048096},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3220589756965637}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8025602102279663},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.6466807723045349},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6051461100578308},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5980455875396729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5839444994926453},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5493613481521606},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5096578598022461},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44671177864074707},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.43869125843048096},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3220589756965637},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/14727978251314557","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978251314557","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2774921310","https://openalex.org/W2791740949","https://openalex.org/W2902708155","https://openalex.org/W2907226170","https://openalex.org/W2911484868","https://openalex.org/W2943225621","https://openalex.org/W3006282221","https://openalex.org/W3006560346","https://openalex.org/W3008297311","https://openalex.org/W3012462861","https://openalex.org/W3029029935","https://openalex.org/W3039027785","https://openalex.org/W3102707396","https://openalex.org/W3198068131","https://openalex.org/W4205152111","https://openalex.org/W4210623501","https://openalex.org/W4213422856","https://openalex.org/W4225415777","https://openalex.org/W4285114122","https://openalex.org/W4286216524","https://openalex.org/W4289351943","https://openalex.org/W4292543379","https://openalex.org/W4296716476","https://openalex.org/W4308698170","https://openalex.org/W4309045431","https://openalex.org/W4321105107","https://openalex.org/W4381741534","https://openalex.org/W4387535246","https://openalex.org/W4388180165","https://openalex.org/W4388854102"],"related_works":["https://openalex.org/W2599472179","https://openalex.org/W4323057981","https://openalex.org/W4375867731","https://openalex.org/W3178607569","https://openalex.org/W4310870954","https://openalex.org/W4285161415","https://openalex.org/W3099765033","https://openalex.org/W2997155179","https://openalex.org/W4382052965","https://openalex.org/W4387090791"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,40,46,49,59,65,70,77,87,90,96,99,106,110,115,118,127,134,157,161,202,209],"automatic":[4,177],"recognition":[5,67,135,158,178],"system":[6,17,91,136,163,179],"of":[7,69,89,150,160,205],"vocal":[8,22,34,84,166,181],"performance":[9,23,122,167,182],"style":[10],"based":[11,38,137],"on":[12,39,126,138,171],"residual":[13],"network":[14],"(ResNet).":[15],"The":[16,130],"can":[18],"precisely":[19],"recognize":[20],"multiple":[21,33],"styles":[24,35,168,183],"through":[25],"automation":[26],"technology.":[27],"Firstly,":[28],"an":[29,176,187],"audio":[30,81],"dataset":[31,43,50,100],"covering":[32],"was":[36,51,62,73,92,101,123,169],"constructed":[37],"publicly":[41],"available":[42],"GTZAN,":[44],"and":[45,83,109,145,153,189],"data":[47],"in":[48,142,192,208],"preprocessed":[52],"to":[53,75,175],"extract":[54],"key":[55],"music":[56,210],"features.":[57],"Subsequently,":[58],"ResNet":[60,139,174],"model":[61,116],"chosen":[63],"as":[64],"core":[66],"component":[68],"system,":[71],"which":[72],"trained":[74],"learn":[76],"complex":[78],"relationship":[79],"between":[80],"features":[82],"styles.":[85],"Finally,":[86],"construction":[88],"carried":[93],"out.":[94],"In":[95],"verification":[97],"phase,":[98],"divided":[102],"into":[103],"two":[104],"parts:":[105],"training":[107,114,119],"set":[108],"test":[111,128],"set.":[112,129],"After":[113],"using":[117],"set,":[120],"its":[121],"comprehensively":[124],"evaluated":[125],"experiment":[131],"showed":[132],"that":[133],"performed":[140],"well":[141],"precision,":[143],"recall,":[144],"accuracy,":[146],"with":[147],"specific":[148],"values":[149],"95.6%,":[151],"91.6%,":[152],"96.7%,":[154],"respectively.":[155],"Meanwhile,":[156],"accuracy":[159],"ResNet-based":[162],"for":[164,180,201],"10":[165],"95.96%":[170],"average.":[172],"Applying":[173],"not":[184],"only":[185],"provides":[186],"efficient":[188],"reliable":[190],"solution":[191],"this":[193],"field,":[194],"but":[195],"also":[196],"opens":[197],"up":[198],"new":[199],"horizons":[200],"further":[203],"application":[204],"deep":[206],"learning":[207],"industry.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}