{"id":"https://openalex.org/W4391341350","doi":"https://doi.org/10.1109/jbhi.2024.3360151","title":"Generative Listener EEG for Speech Emotion Recognition Using Generative Adversarial Networks With Compressed Sensing","display_name":"Generative Listener EEG for Speech Emotion Recognition Using Generative Adversarial Networks With Compressed Sensing","publication_year":2024,"publication_date":"2024-01-30","ids":{"openalex":"https://openalex.org/W4391341350","doi":"https://doi.org/10.1109/jbhi.2024.3360151","pmid":"https://pubmed.ncbi.nlm.nih.gov/38289847"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2024.3360151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2024.3360151","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101829426","display_name":"Chang Jiang","orcid":"https://orcid.org/0000-0001-9726-902X"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Chang","raw_affiliation_strings":["Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0001-9726-902X","affiliations":[{"raw_affiliation_string":"Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643824","display_name":"Zhixin Zhang","orcid":"https://orcid.org/0009-0006-6520-4129"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixin Zhang","raw_affiliation_strings":["Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0006-6520-4129","affiliations":[{"raw_affiliation_string":"Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102727148","display_name":"Zelin Wang","orcid":"https://orcid.org/0009-0003-5405-7432"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zelin Wang","raw_affiliation_strings":["Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0003-5405-7432","affiliations":[{"raw_affiliation_string":"Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102873457","display_name":"Jiacheng Li","orcid":"https://orcid.org/0009-0008-7265-5985"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiacheng Li","raw_affiliation_strings":["Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0008-7265-5985","affiliations":[{"raw_affiliation_string":"Institute of Big Data Science and Industry, the School of Computer and Information Technology, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101833358","display_name":"Linsheng Meng","orcid":"https://orcid.org/0009-0003-3255-2416"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linsheng Meng","raw_affiliation_strings":["School of Physical Education, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0003-3255-2416","affiliations":[{"raw_affiliation_string":"School of Physical Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100689959","display_name":"Pan Lin","orcid":"https://orcid.org/0000-0001-7473-905X"},"institutions":[{"id":"https://openalex.org/I173759888","display_name":"Hunan Normal University","ror":"https://ror.org/053w1zy07","country_code":"CN","type":"education","lineage":["https://openalex.org/I173759888"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Lin","raw_affiliation_strings":["Center for Mind&amp;Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, China","Center for Mind&Brain Sciences and institute of Interdisciplinary Studies, Hunan Normal University, Hunan, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-7473-905X","affiliations":[{"raw_affiliation_string":"Center for Mind&amp;Brain Sciences and Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, China","institution_ids":["https://openalex.org/I173759888"]},{"raw_affiliation_string":"Center for Mind&Brain Sciences and institute of Interdisciplinary Studies, Hunan Normal University, Hunan, Changsha, China","institution_ids":["https://openalex.org/I173759888"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3785,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92979736,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"28","issue":"4","first_page":"2025","last_page":"2036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"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/T10860","display_name":"Speech and Audio Processing","score":0.9987999796867371,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7281376123428345},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7207878232002258},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6373202800750732},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5838376879692078},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.548995852470398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4685830771923065},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4649328887462616},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35050323605537415},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.19628354907035828},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.18334388732910156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281376123428345},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7207878232002258},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6373202800750732},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5838376879692078},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.548995852470398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4685830771923065},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4649328887462616},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35050323605537415},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.19628354907035828},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.18334388732910156},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2024.3360151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2024.3360151","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:38289847","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38289847","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G8734624840","display_name":"\u57fa\u4e8e\u591a\u6a21\u6001\u6838\u78c1\u5171\u632f\u6210\u50cf\u6280\u672f\u7684\u989d\u53f6\uff0d\u7eb9\u72b6\u4f53\u8ba4\u77e5\u63a7\u5236\u5927\u8111\u5de5\u4f5c\u673a\u5236\u7814\u7a76","funder_award_id":"62071177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2064059030","https://openalex.org/W2073791557","https://openalex.org/W2093640073","https://openalex.org/W2105159663","https://openalex.org/W2111037713","https://openalex.org/W2119667497","https://openalex.org/W2125389028","https://openalex.org/W2592497314","https://openalex.org/W2742589445","https://openalex.org/W2792071143","https://openalex.org/W2898664946","https://openalex.org/W2913144232","https://openalex.org/W2955221632","https://openalex.org/W2980292555","https://openalex.org/W3023563170","https://openalex.org/W3088256290","https://openalex.org/W3092019167","https://openalex.org/W3107620895","https://openalex.org/W3157504026","https://openalex.org/W3197261948","https://openalex.org/W3205820451","https://openalex.org/W3209313354","https://openalex.org/W3210840341","https://openalex.org/W4250955649","https://openalex.org/W4384155732","https://openalex.org/W6676605431","https://openalex.org/W6678815747"],"related_works":["https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4377980832","https://openalex.org/W3126677997","https://openalex.org/W2897769091","https://openalex.org/W1610857240","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4235873501"],"abstract_inverted_index":{"Currently,":[0],"emotional":[1,30,57,70,157],"features":[2],"in":[3,59,73,89,160,198,219],"speech":[4,114],"emotion":[5,100,200,221],"recognition":[6,14,201],"are":[7],"typically":[8],"extracted":[9],"from":[10],"the":[11,129,136,141,156,161,169,175,179,186,204,214],"speeches,":[12],"However,":[13],"accuracy":[15],"can":[16],"be":[17,48],"influenced":[18],"by":[19,189,196],"factors":[20],"such":[21],"as":[22,64],"semantics,":[23],"language,":[24],"and":[25,55,115,138],"cross-speech":[26],"datasets.":[27],"Achieving":[28],"consistent":[29],"judgment":[31],"with":[32],"human":[33],"listeners":[34],"is":[35],"a":[36,65,80,92,110,151],"key":[37],"challenge":[38],"for":[39,68,213],"AI":[40],"to":[41,47,91,108,117,154,173],"address.":[42],"Electroencephalography":[43],"(EEG)":[44],"signals":[45],"prove":[46],"an":[49,207],"effective":[50],"means":[51],"of":[52,140,178,209,216],"capturing":[53],"authentic":[54],"meaningful":[56],"information":[58],"humans.":[60],"This":[61],"positions":[62],"EEG":[63,131],"promising":[66],"tool":[67],"detecting":[69],"cues":[71],"conveyed":[72,159],"speech.":[74,162],"In":[75],"this":[76,190,217],"study,":[77],"we":[78,122,167],"proposed":[79],"novel":[81],"approach":[82],"named":[83],"CS-GAN":[84],"that":[85,185],"generates":[86],"listener":[87,194],"EEGs":[88,116,146,188,195],"response":[90],"speaker's":[93],"speech,":[94],"specifically":[95],"aimed":[96],"at":[97],"enhancing":[98,135],"cross-subject":[99,176,199,220],"recognition.":[101,222],"We":[102],"utilized":[103],"generative":[104],"adversarial":[105],"networks":[106],"(GANs)":[107],"establish":[109],"mapping":[111],"relationship":[112],"between":[113],"generate":[118],"stimulus-induced":[119],"EEGs.":[120,143],"Furthermore,":[121,203],"integrated":[123],"compressive":[124],"sensing":[125],"theory":[126],"(CS)":[127],"into":[128],"GAN-based":[130],"generation":[132],"method,":[133],"thereby":[134],"fidelity":[137],"diversity":[139],"generated":[142,145,187],"The":[144,181],"were":[147],"then":[148],"processed":[149],"using":[150],"CNN-LSTM":[152],"model":[153],"identify":[155],"categories":[158],"By":[163],"averaging":[164],"these":[165],"EEGs,":[166],"obtained":[168],"event-related":[170],"potentials":[171],"(ERPs)":[172],"improve":[174],"capability":[177],"method.":[180],"experimental":[182],"results":[183],"demonstrate":[184],"method":[191,218],"outperform":[192],"real":[193],"9.31%":[197],"tasks.":[202],"ERPs":[205],"show":[206],"improvement":[208],"43.59%,":[210],"providing":[211],"evidence":[212],"effectiveness":[215]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
