{"id":"https://openalex.org/W2977445866","doi":"https://doi.org/10.1109/ijcnn.2019.8851935","title":"Sequencing the musical sections with deep learning","display_name":"Sequencing the musical sections with deep learning","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977445866","doi":"https://doi.org/10.1109/ijcnn.2019.8851935","mag":"2977445866"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5087684635","display_name":"Xuange Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuange Cui","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016458854","display_name":"Mingxue Liao","orcid":"https://orcid.org/0000-0001-6928-6885"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxue Liao","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041894655","display_name":"Pin Lv","orcid":"https://orcid.org/0000-0002-3425-9913"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pin Lv","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062168363","display_name":"Changwen Zheng","orcid":"https://orcid.org/0000-0002-2311-6757"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changwen Zheng","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087684635"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10408739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"521","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","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/T11309","display_name":"Music and Audio Processing","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/T10788","display_name":"Neuroscience and Music Perception","score":0.993399977684021,"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":0.9919999837875366,"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":0.7956695556640625},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.693483293056488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6187869310379028},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5771465301513672},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5326753854751587},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5290540456771851},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5179585218429565},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4963601231575012},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.487490177154541},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4822971820831299},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4775605797767639},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4271080493927002},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4211325943470001},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41010966897010803},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4091196060180664},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3660338819026947},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35738617181777954}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7956695556640625},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.693483293056488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6187869310379028},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5771465301513672},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5326753854751587},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5290540456771851},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5179585218429565},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4963601231575012},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.487490177154541},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4822971820831299},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4775605797767639},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4271080493927002},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4211325943470001},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41010966897010803},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4091196060180664},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3660338819026947},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35738617181777954},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W1825426646","https://openalex.org/W1978421240","https://openalex.org/W2040519441","https://openalex.org/W2042390666","https://openalex.org/W2076769328","https://openalex.org/W2131732106","https://openalex.org/W2139689188","https://openalex.org/W2144707026","https://openalex.org/W2200211686","https://openalex.org/W2295802993","https://openalex.org/W2406222150","https://openalex.org/W2487442924","https://openalex.org/W2508865106","https://openalex.org/W2522453719","https://openalex.org/W2527573165","https://openalex.org/W2563031223","https://openalex.org/W2572771584","https://openalex.org/W2736887001","https://openalex.org/W2747464893","https://openalex.org/W2765760147","https://openalex.org/W2766803997","https://openalex.org/W2767936773","https://openalex.org/W2772600958","https://openalex.org/W2801470297","https://openalex.org/W2809456243","https://openalex.org/W2890491191","https://openalex.org/W2896271387","https://openalex.org/W2897277084","https://openalex.org/W2919115771","https://openalex.org/W2962939524","https://openalex.org/W2962968281","https://openalex.org/W2963181423","https://openalex.org/W2963775347","https://openalex.org/W2964037671","https://openalex.org/W2964069355","https://openalex.org/W2964151830","https://openalex.org/W4294554810","https://openalex.org/W4300577530","https://openalex.org/W6638791942","https://openalex.org/W6697455664","https://openalex.org/W6713563955","https://openalex.org/W6725015247","https://openalex.org/W6726985591","https://openalex.org/W6741185346","https://openalex.org/W6743059557","https://openalex.org/W6746401785","https://openalex.org/W6746773890","https://openalex.org/W6754200190","https://openalex.org/W6760385162","https://openalex.org/W6766016090"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W3199964822","https://openalex.org/W4232132981","https://openalex.org/W4238046985","https://openalex.org/W3164948662","https://openalex.org/W3003242282","https://openalex.org/W3153597579","https://openalex.org/W3012824888"],"abstract_inverted_index":{"Deep":[0],"learning":[1,25,33],"has":[2],"become":[3],"increasingly":[4],"popular":[5],"for":[6,117,141],"sequence":[7],"modeling":[8],"in":[9,130,165],"various":[10],"domains.":[11],"In":[12],"this":[13,136],"work,":[14],"we":[15,77,98],"address":[16],"the":[17,37,48,61,66,79,84,89,92,100,107,111,139,142,149,154,160],"musical":[18,58],"order":[19,118],"verification":[20],"as":[21,36,60,69,83],"a":[22,29,70,74],"sequential":[23],"pattern":[24],"task.":[26],"We":[27,55],"present":[28],"more":[30],"advanced":[31],"self-supervised":[32],"model,":[34],"dubbed":[35],"triple-wise":[38,57],"similarity":[39,90],"with":[40],"recurrent":[41],"neural":[42],"networks":[43],"(TSN-R)":[44],"which":[45],"is":[46],"on":[47],"basis":[49],"of":[50,91,132,145,151],"state-of-the-art":[51],"Similarity":[52],"Embedding":[53],"Network.":[54],"take":[56],"sections":[59],"input":[62,85],"instance,":[63],"and":[64,87,159],"leverage":[65],"temporal":[67],"coherence":[68],"supervisory":[71],"signal.":[72],"As":[73],"first":[75],"step,":[76],"use":[78],"triplet":[80,93],"Siamese":[81],"network":[82],"layer,":[86],"assess":[88],"feature":[94],"maps.":[95],"After":[96],"that,":[97],"choose":[99],"bidirectional":[101],"LSTM":[102],"to":[103],"extract":[104],"features":[105],"along":[106],"time":[108],"dimension.":[109],"Finally,":[110],"subsequent":[112],"fully-connected":[113],"layers":[114],"are":[115,163],"used":[116],"verification.":[119],"The":[120],"experiments":[121],"show":[122],"that":[123],"our":[124,146,166],"approach":[125],"outperforms":[126],"other":[127],"competing":[128],"models":[129,158],"terms":[131],"prediction":[133],"accuracy.":[134],"Additionally,":[135],"paper":[137],"reveals":[138],"reasons":[140],"good":[143],"performance":[144],"model":[147],"through":[148],"2d-visualization":[150],"features.":[152],"All":[153],"source":[155],"code,":[156],"pre-trained":[157],"experiment":[161],"results":[162],"available":[164],"project":[167],"page.":[168],"https://github.com/ISCASTEAM/Sequencing-the-musical-sections.":[169]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}