{"id":"https://openalex.org/W4403722466","doi":"https://doi.org/10.1109/access.2024.3486003","title":"Split-Attention CNN and Self-Attention With RoPE and GCN for Voice Activity Detection","display_name":"Split-Attention CNN and Self-Attention With RoPE and GCN for Voice Activity Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403722466","doi":"https://doi.org/10.1109/access.2024.3486003"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3486003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3486003","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3486003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003356365","display_name":"YingWei Tan","orcid":"https://orcid.org/0000-0003-0944-118X"},"institutions":[{"id":"https://openalex.org/I8659980","display_name":"Volkswagen Group (United States)","ror":"https://ror.org/034e5n787","country_code":"US","type":"company","lineage":["https://openalex.org/I1319473763","https://openalex.org/I8659980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingwei Tan","raw_affiliation_strings":["Volkswagen-Mobvoi (Beijing) Information Technology Company Ltd., Beijing, China","Volkswagen-Mobvoi (BeiJing) Information Technology Co., Ltd, BeiJing, China"],"raw_orcid":"https://orcid.org/0000-0003-0944-118X","affiliations":[{"raw_affiliation_string":"Volkswagen-Mobvoi (Beijing) Information Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I8659980"]},{"raw_affiliation_string":"Volkswagen-Mobvoi (BeiJing) Information Technology Co., Ltd, BeiJing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Xuefeng Ding","orcid":"https://orcid.org/0009-0009-0007-3916"},"institutions":[{"id":"https://openalex.org/I8659980","display_name":"Volkswagen Group (United States)","ror":"https://ror.org/034e5n787","country_code":"US","type":"company","lineage":["https://openalex.org/I1319473763","https://openalex.org/I8659980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuefeng Ding","raw_affiliation_strings":["Volkswagen-Mobvoi (Beijing) Information Technology Company Ltd., Beijing, China","Volkswagen-Mobvoi (BeiJing) Information Technology Co., Ltd, BeiJing, China"],"raw_orcid":"https://orcid.org/0009-0009-0007-3916","affiliations":[{"raw_affiliation_string":"Volkswagen-Mobvoi (Beijing) Information Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I8659980"]},{"raw_affiliation_string":"Volkswagen-Mobvoi (BeiJing) Information Technology Co., Ltd, BeiJing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8659980"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.3892,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84473941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"156673","last_page":"156682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.96670001745224,"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":0.96670001745224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955533623695374},{"id":"https://openalex.org/keywords/rope","display_name":"Rope","score":0.6045475602149963},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5572574138641357}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955533623695374},{"id":"https://openalex.org/C162269090","wikidata":"https://www.wikidata.org/wiki/Q1156047","display_name":"Rope","level":2,"score":0.6045475602149963},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5572574138641357},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3486003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3486003","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9241216e1fe44efcbb0abfd43e21d8e2","is_oa":true,"landing_page_url":"https://doaj.org/article/9241216e1fe44efcbb0abfd43e21d8e2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 156673-156682 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3486003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3486003","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1563939609","https://openalex.org/W1905983571","https://openalex.org/W1965559434","https://openalex.org/W1974387177","https://openalex.org/W1985242443","https://openalex.org/W1993911116","https://openalex.org/W2032596349","https://openalex.org/W2065238411","https://openalex.org/W2075390205","https://openalex.org/W2098265087","https://openalex.org/W2108819501","https://openalex.org/W2115717467","https://openalex.org/W2120979206","https://openalex.org/W2129120544","https://openalex.org/W2145524159","https://openalex.org/W2145887942","https://openalex.org/W2162520685","https://openalex.org/W2170644918","https://openalex.org/W2197404611","https://openalex.org/W2240641835","https://openalex.org/W2301105650","https://openalex.org/W2510670092","https://openalex.org/W2558748708","https://openalex.org/W2752782242","https://openalex.org/W2791616807","https://openalex.org/W2885307078","https://openalex.org/W2917987043","https://openalex.org/W2922509574","https://openalex.org/W2954930777","https://openalex.org/W2963242190","https://openalex.org/W2964015378","https://openalex.org/W2995588677","https://openalex.org/W3016719260","https://openalex.org/W3024085360","https://openalex.org/W3160747466","https://openalex.org/W3160984956","https://openalex.org/W3161282967","https://openalex.org/W4281554565","https://openalex.org/W4307135244","https://openalex.org/W4372262623","https://openalex.org/W4372344102","https://openalex.org/W4392307944","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6780226713","https://openalex.org/W6793987055","https://openalex.org/W6798483980","https://openalex.org/W6810763489"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2382190654","https://openalex.org/W2041034200","https://openalex.org/W2373129217","https://openalex.org/W1924903628","https://openalex.org/W2375717371","https://openalex.org/W4390286213","https://openalex.org/W2372453219"],"abstract_inverted_index":{"In":[0,73],"recent":[1],"years,":[2],"attention-based":[3],"voice":[4,83,226,234],"activity":[5,84,227,235],"detection":[6,85,228,236],"systems":[7,249],"have":[8],"become":[9],"popular,":[10],"attributed":[11],"to":[12,15,128,144,169],"their":[13,131],"ability":[14],"encapsulate":[16],"a":[17,45,78,124,151,160,184,201,211],"diverse":[18,139],"array":[19],"of":[20,25,40,51,113,123,165,218,244],"contextual":[21],"information.":[22],"The":[23,38,238],"integration":[24],"multi-head":[26],"attention":[27,33,42,119,157,174],"and":[28,92,99,137,232],"position":[29,55,97,180,189,208],"embedding":[30,56,98],"within":[31,69],"the":[32,52,62,70,111,163,197,216,242],"architecture":[34,81],"holds":[35],"pivotal":[36],"importance.":[37],"employment":[39],"multiple":[41],"heads":[43],"enables":[44],"differential":[46],"emphasis":[47],"on":[48,130,224],"distinct":[49],"segments":[50],"sequence,":[53],"whereas":[54],"offers":[57],"crucial":[58],"guidance":[59],"in":[60,104,133,142],"modeling":[61],"dependencies":[63],"among":[64,172],"elements":[65],"occupying":[66],"various":[67,121,251],"positions":[68],"input":[71,198],"sequence.":[72],"this":[74],"work,":[75],"we":[76,116,149,182,221],"propose":[77],"new":[79],"hybrid":[80],"for":[82,109,177],"incorporating":[86],"both":[87],"split-attention":[88],"convolutional":[89,101,125,167],"neural":[90,126],"network":[91,127],"self-attention":[93,212],"layers":[94],"with":[95],"rotary":[96,188],"graph":[100,166],"networks,":[102],"trained":[103],"an":[105],"end-to-end":[106],"manner.":[107],"Firstly,":[108],"enhancing":[110],"learning":[112,138,178],"local":[114],"features,":[115,148],"introduce":[117],"channel-wise":[118],"across":[120,250],"branches":[122],"capitalize":[129],"proficiency":[132],"capturing":[134],"cross-feature":[135],"interactions":[136],"representations.":[140],"Furthermore,":[141],"order":[143],"better":[145],"learn":[146],"global":[147],"present":[150],"novel":[152],"approach":[153],"that":[154],"treats":[155],"each":[156],"head":[158],"as":[159],"node,":[161],"enabling":[162],"utilization":[164],"networks":[168],"identify":[170],"correlations":[171],"these":[173],"heads.":[175],"Lastly,":[176],"relative":[179,207],"information,":[181],"employ":[183],"cutting-edge":[185],"implementation":[186],"named":[187],"embedding,":[190],"which":[191],"encodes":[192],"absolute":[193],"positional":[194],"information":[195,209],"into":[196,210],"sequence":[199],"via":[200],"rotation":[202],"matrix,":[203],"seamlessly":[204],"integrating":[205],"explicit":[206],"module.":[213],"To":[214],"assess":[215],"effectiveness":[217],"our":[219,245],"method,":[220],"conduct":[222],"experiments":[223],"synthetic":[225],"datasets,":[229,231],"AVA-speech":[230],"Kaggle":[233],"datasets.":[237],"results":[239],"obtained":[240],"highlight":[241],"superiority":[243],"method":[246],"over":[247],"baseline":[248],"noise":[252],"conditions.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}