{"id":"https://openalex.org/W3164992579","doi":"https://doi.org/10.1109/ismict51748.2021.9434907","title":"A Multi-Modal Joint Voice Parts Division Method Based On Deep Learning","display_name":"A Multi-Modal Joint Voice Parts Division Method Based On Deep Learning","publication_year":2021,"publication_date":"2021-04-14","ids":{"openalex":"https://openalex.org/W3164992579","doi":"https://doi.org/10.1109/ismict51748.2021.9434907","mag":"3164992579"},"language":"en","primary_location":{"id":"doi:10.1109/ismict51748.2021.9434907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismict51748.2021.9434907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 15th International Symposium on Medical Information and Communication Technology (ISMICT)","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/A5016606322","display_name":"Lingjun Chen","orcid":"https://orcid.org/0000-0001-7064-6999"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingjun Chen","raw_affiliation_strings":["XiaMen University, XiaMen, China"],"affiliations":[{"raw_affiliation_string":"XiaMen University, XiaMen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103097681","display_name":"Caidan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caidan Zhao","raw_affiliation_strings":["XiaMen University, XiaMen, China"],"affiliations":[{"raw_affiliation_string":"XiaMen University, XiaMen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101618416","display_name":"Yunyi Liu","orcid":"https://orcid.org/0000-0002-3065-9872"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyi Liu","raw_affiliation_strings":["XiaMen University, XiaMen, China"],"affiliations":[{"raw_affiliation_string":"XiaMen University, XiaMen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103227776","display_name":"Peiyun Zhuang","orcid":"https://orcid.org/0000-0002-5946-1173"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peiyun Zhuang","raw_affiliation_strings":["XiaMen University, XiaMen, China"],"affiliations":[{"raw_affiliation_string":"XiaMen University, XiaMen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016606322"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52379918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"47","issue":null,"first_page":"35","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9958000183105469,"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/T11309","display_name":"Music and Audio Processing","score":0.9811000227928162,"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/division","display_name":"Division (mathematics)","score":0.7841265201568604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7306362986564636},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.688346266746521},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6718541979789734},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47047072649002075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4489988088607788},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3504296541213989},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15863332152366638},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.08982977271080017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08442619442939758},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.07629126310348511}],"concepts":[{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.7841265201568604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306362986564636},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.688346266746521},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6718541979789734},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47047072649002075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4489988088607788},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3504296541213989},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15863332152366638},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.08982977271080017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08442619442939758},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.07629126310348511},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ismict51748.2021.9434907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismict51748.2021.9434907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 15th International Symposium on Medical Information and Communication Technology (ISMICT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6600000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W755826933","https://openalex.org/W1531696119","https://openalex.org/W1979242074","https://openalex.org/W1990079834","https://openalex.org/W2007757953","https://openalex.org/W2015615135","https://openalex.org/W2018608907","https://openalex.org/W2057981416","https://openalex.org/W2065181214","https://openalex.org/W2151572393","https://openalex.org/W2162109146","https://openalex.org/W2726644425","https://openalex.org/W2772940218","https://openalex.org/W2911380243","https://openalex.org/W2966793900","https://openalex.org/W2969640511","https://openalex.org/W3152128808","https://openalex.org/W6654333452","https://openalex.org/W6682606512"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4213091376","https://openalex.org/W4252317921","https://openalex.org/W2038973998","https://openalex.org/W2033939734","https://openalex.org/W243046325","https://openalex.org/W1975640583","https://openalex.org/W3094080891","https://openalex.org/W2330973770","https://openalex.org/W1979495818"],"abstract_inverted_index":{"The":[0,112],"division":[1,75],"of":[2,66,95,114],"singers'":[3,28,56,84],"voice":[4,19,41,57,73,85,96],"parts":[5,20,42,74],"is":[6,80,104,141],"a":[7,24,72],"basic":[8],"problem":[9],"in":[10,126],"vocal":[11,15],"arts":[12],"medicine":[13],"and":[14,47,59,98,108,122,136],"music":[16],"teaching.":[17],"Improper":[18],"classification":[21,139],"can":[22],"have":[23],"negative":[25],"impact":[26],"on":[27],"health.":[29],"In":[30,87],"this":[31,91,110,127],"work,":[32],"we":[33],"propose":[34],"an":[35],"objective":[36],"method":[37],"to":[38,82,89,106],"classify":[39],"the":[40,44,64,119,137],"from":[43,55,101],"acoustic":[45],"perspective":[46],"anatomic":[48],"perspective.":[49],"We":[50],"first":[51],"extract":[52],"relevant":[53],"features":[54,65],"signals":[58,97],"laryngoscope":[60],"images,":[61],"then":[62],"splice":[63],"these":[67],"two":[68],"modalities.":[69],"After":[70],"that,":[71],"convolutional":[76],"network":[77,123],"(VDCNN)":[78],"model":[79,128],"constructed":[81],"evaluate":[83],"categories.":[86],"order":[88],"realize":[90],"model,":[92],"real":[93],"data":[94],"laryngeal":[99],"images":[100],"74":[102],"singers":[103],"applied":[105],"train":[107],"adjust":[109],"model.":[111],"analysis":[113],"experimental":[115],"results":[116],"shows":[117],"that":[118],"characteristic":[120],"parameters":[121],"structure":[124],"used":[125],"are":[129],"significantly":[130],"improved":[131],"compared":[132],"with":[133],"similar":[134],"methods,":[135],"optimal":[138],"accuracy":[140],"93.17%.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
