{"id":"https://openalex.org/W4391306048","doi":"https://doi.org/10.1109/smc53992.2023.10394150","title":"Enhancing Subject-Independent EEG-Based Auditory Attention Decoding with WGAN and Pearson Correlation Coefficient","display_name":"Enhancing Subject-Independent EEG-Based Auditory Attention Decoding with WGAN and Pearson Correlation Coefficient","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4391306048","doi":"https://doi.org/10.1109/smc53992.2023.10394150"},"language":"en","primary_location":{"id":"doi:10.1109/smc53992.2023.10394150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53992.2023.10394150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5082298285","display_name":"Saurav Pahuja","orcid":"https://orcid.org/0000-0003-1170-5199"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Saurav Pahuja","raw_affiliation_strings":["University of Bremen,Machine Listening Lab (MLL),Germany","Machine Listening Lab (MLL), University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Machine Listening Lab (MLL),Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"Machine Listening Lab (MLL), University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020039763","display_name":"Gabriel Ivucic","orcid":"https://orcid.org/0000-0003-4189-0348"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gabriel Ivucic","raw_affiliation_strings":["University of Bremen,Cognitive Systems Lab (CSL),Germany","Cognitive Systems Lab (CSL), University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Cognitive Systems Lab (CSL),Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"Cognitive Systems Lab (CSL), University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010913778","display_name":"Felix Putze","orcid":"https://orcid.org/0000-0001-5203-8797"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix Putze","raw_affiliation_strings":["University of Bremen,Cognitive Systems Lab (CSL),Germany","Cognitive Systems Lab (CSL), University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Cognitive Systems Lab (CSL),Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"Cognitive Systems Lab (CSL), University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088380372","display_name":"Siqi Cai","orcid":"https://orcid.org/0000-0003-3282-9246"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Siqi Cai","raw_affiliation_strings":["National University of Singapore,Department of Electrical and Computer Engineering,Singapore","Department of Electrical and Computer Engineering, National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore,Department of Electrical and Computer Engineering,Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032690182","display_name":"Haizhou Li","orcid":"https://orcid.org/0000-0001-9158-9401"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]},{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN","DE","SG"],"is_corresponding":false,"raw_author_name":"Haizhou Li","raw_affiliation_strings":["University of Bremen,Machine Listening Lab (MLL),Germany","Kriston AI, Xiamen, China","Department of Electrical and Computer Engineering, National University of Singapore, Singapore","Machine Listening Lab (MLL), University of Bremen, Germany","Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Machine Listening Lab (MLL),Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"Kriston AI, Xiamen, China","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Machine Listening Lab (MLL), University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I4210099586"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058049725","display_name":"Tanja Schultz","orcid":"https://orcid.org/0000-0002-9809-7028"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tanja Schultz","raw_affiliation_strings":["University of Bremen,Cognitive Systems Lab (CSL),Germany","CSL and hosts MLL","Cognitive Systems Lab (CSL), University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Cognitive Systems Lab (CSL),Germany","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"CSL and hosts MLL","institution_ids":[]},{"raw_affiliation_string":"Cognitive Systems Lab (CSL), University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4929,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64737319,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3715","last_page":"3720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9995999932289124,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.7622466087341309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7215928435325623},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6730110049247742},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6300822496414185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.586132824420929},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5493563413619995},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48107051849365234},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.4699663817882538},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.46698397397994995},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.46156516671180725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4532011151313782},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.45254939794540405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41046249866485596},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20915007591247559},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1584351360797882},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14804348349571228},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08324474096298218}],"concepts":[{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.7622466087341309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7215928435325623},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6730110049247742},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6300822496414185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.586132824420929},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5493563413619995},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48107051849365234},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.4699663817882538},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.46698397397994995},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.46156516671180725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4532011151313782},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.45254939794540405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41046249866485596},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20915007591247559},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1584351360797882},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14804348349571228},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08324474096298218},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53992.2023.10394150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53992.2023.10394150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5088964179","display_name":null,"funder_award_id":"T00120220002","funder_id":"https://openalex.org/F4320331102","funder_display_name":"Shenzhen Research Institute of Big Data"},{"id":"https://openalex.org/G822767079","display_name":null,"funder_award_id":"GRK2739/1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8856801985","display_name":null,"funder_award_id":"B10120210117-KP02","funder_id":"https://openalex.org/F4320322170","funder_display_name":"University of Hong Kong"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320322170","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86"},{"id":"https://openalex.org/F4320324729","display_name":"Universit\u00e4t Bremen","ror":"https://ror.org/04ers2y35"},{"id":"https://openalex.org/F4320331102","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1574447377","https://openalex.org/W1965072918","https://openalex.org/W1991139021","https://openalex.org/W2027250573","https://openalex.org/W2082183045","https://openalex.org/W2157617037","https://openalex.org/W2158904676","https://openalex.org/W2520029811","https://openalex.org/W2559655401","https://openalex.org/W2766313107","https://openalex.org/W2771075519","https://openalex.org/W2962909949","https://openalex.org/W2963355311","https://openalex.org/W2963684088","https://openalex.org/W2990701861","https://openalex.org/W3125807224","https://openalex.org/W3126966983","https://openalex.org/W3159696612","https://openalex.org/W3162043918","https://openalex.org/W3209575302","https://openalex.org/W4206654584","https://openalex.org/W4206798246","https://openalex.org/W4309344694","https://openalex.org/W6685352114","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W357196361","https://openalex.org/W2027314909","https://openalex.org/W1036938216","https://openalex.org/W3109425891","https://openalex.org/W2113714434","https://openalex.org/W3096637473","https://openalex.org/W2377792686","https://openalex.org/W4200439127","https://openalex.org/W829658220","https://openalex.org/W2946560178"],"abstract_inverted_index":{"Electroencephalography":[0],"(EEG)":[1],"related":[2],"research":[3],"faces":[4],"a":[5,50,80,103,145,155],"significant":[6],"challenge":[7],"of":[8,62,107,125,182],"subject":[9],"independence":[10],"due":[11],"to":[12,52,86,158,176],"the":[13,53,58,94,133,170,174,178],"variation":[14],"in":[15,28,116,141,162],"brain":[16],"signals":[17],"and":[18,40,60,112,128,180],"responses":[19],"among":[20],"individuals.":[21],"While":[22],"deep":[23,74,152],"learning":[24,153],"models":[25],"hold":[26],"promise":[27],"addressing":[29],"this":[30,46,100],"challenge,":[31],"their":[32],"effectiveness":[33],"depends":[34],"on":[35,102,167],"large":[36],"datasets":[37],"for":[38,65,144],"training":[39,63,122],"generalization":[41,179],"across":[42],"participants.":[43],"To":[44],"overcome":[45],"limitation,":[47],"we":[48],"propose":[49],"solution":[51],"above":[54],"limitation":[55],"by":[56,132],"increasing":[57],"size":[59],"quality":[61],"data":[64,130,160],"subject-independent":[66,117,163],"auditory":[67,109],"attention":[68,110],"decoding":[69],"(AAD)":[70],"using":[71],"EEG":[72,183],"with":[73,90],"learning.":[75],"Specifically,":[76],"our":[77],"method":[78,101,172],"employs":[79],"Wasserstein":[81],"Generative":[82],"Adversarial":[83],"Network":[84],"(WGAN)":[85],"generate":[87],"synthetic":[88],"data,":[89],"Pearson":[91],"correlation":[92],"filtering":[93],"most":[95],"realistic":[96],"samples.":[97],"We":[98],"evaluated":[99],"publicly":[104],"available":[105],"dataset":[106],"selective":[108],"experiments":[111],"showed":[113],"superior":[114],"performance":[115],"AAD":[118,142,164],"performance.":[119],"The":[120],"mixed":[121],"set,":[123],"consisting":[124],"both":[126],"real":[127],"artificial":[129],"generated":[131],"WGAN+Pearson":[134],"Correlation":[135],"Coefficient,":[136],"demonstrated":[137],"approximately":[138],"4%":[139],"improvement":[140],"accuracy":[143],"1-second":[146],"window.":[147],"These":[148],"results":[149],"demonstrate":[150],"that":[151],"remains":[154],"viable":[156],"approach":[157],"overcoming":[159],"scarcity":[161],"tasks":[165],"based":[166],"EEG.":[168],"Moreover,":[169],"proposed":[171],"has":[173],"potential":[175],"improve":[177],"reliability":[181],"classification":[184],"tasks.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}