{"id":"https://openalex.org/W4225308041","doi":"https://doi.org/10.1109/icassp43922.2022.9746011","title":"Csenet: Complex Squeeze-and-Excitation Network for Speech Depression Level Prediction","display_name":"Csenet: Complex Squeeze-and-Excitation Network for Speech Depression Level Prediction","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4225308041","doi":"https://doi.org/10.1109/icassp43922.2022.9746011"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746011","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5037493212","display_name":"Cunhang Fan","orcid":"https://orcid.org/0000-0001-6318-8803"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cunhang Fan","raw_affiliation_strings":["Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026466982","display_name":"Zhao Lv","orcid":"https://orcid.org/0000-0003-4530-4422"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Lv","raw_affiliation_strings":["Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010724446","display_name":"Shengbing Pei","orcid":"https://orcid.org/0000-0002-7629-7459"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengbing Pei","raw_affiliation_strings":["Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University,Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology,Hefei,China,230601","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079696396","display_name":"Mingyue Niu","orcid":"https://orcid.org/0000-0002-4977-3202"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyue Niu","raw_affiliation_strings":["Tianjin Normal University,School of Computer and Information Engineering,Tianjin,China,300387"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin Normal University,School of Computer and Information Engineering,Tianjin,China,300387","institution_ids":["https://openalex.org/I15062923"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0342,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.93039216,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"546","last_page":"550"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9914000034332275,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9801999926567078,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.9175499677658081},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6852089166641235},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6631994247436523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470998525619507},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6222643256187439},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6122432947158813},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5358537435531616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5056509971618652},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48368388414382935},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46750009059906006},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1973510980606079},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12458255887031555}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.9175499677658081},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6852089166641235},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6631994247436523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470998525619507},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6222643256187439},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6122432947158813},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5358537435531616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5056509971618652},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48368388414382935},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46750009059906006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1973510980606079},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12458255887031555},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746011","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326873","display_name":"National Laboratory of Pattern Recognition","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1976066595","https://openalex.org/W1988088279","https://openalex.org/W2017713202","https://openalex.org/W2045396822","https://openalex.org/W2056403322","https://openalex.org/W2060779380","https://openalex.org/W2070126272","https://openalex.org/W2146890278","https://openalex.org/W2148822124","https://openalex.org/W2194775991","https://openalex.org/W2736814566","https://openalex.org/W2752782242","https://openalex.org/W2805409402","https://openalex.org/W2947078770","https://openalex.org/W2973178409","https://openalex.org/W3010851250","https://openalex.org/W3017138616","https://openalex.org/W3094259155","https://openalex.org/W3095858789","https://openalex.org/W3134427999","https://openalex.org/W3197466182"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W4402568167","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W3127543252","https://openalex.org/W2065606036","https://openalex.org/W2953234277"],"abstract_inverted_index":{"Automatic":[0],"speech":[1,31,50,67,87,112],"depression":[2],"level":[3],"prediction":[4],"(SDLP)":[5],"is":[6,82,107,119],"a":[7,72,100],"very":[8],"challenging":[9],"problem":[10],"in":[11],"affective":[12],"computing.":[13],"There":[14],"are":[15,36],"many":[16],"studies":[17,35],"that":[18],"have":[19],"acquired":[20],"quite":[21],"good":[22],"performances":[23],"for":[24,77,150],"SDLP.":[25,78],"However,":[26],"most":[27],"of":[28,33,66,145],"the":[29,39,44,85,103,115,129,135,143,151],"input":[30,86],"features":[32,51],"these":[34,49],"based":[37],"on":[38,134,158],"amplitude":[40,92],"spectrogram,":[41],"which":[42,89],"loses":[43],"phase":[45,94],"spectrogram":[46,81],"information.":[47],"Therefore,":[48],"may":[52],"lose":[53],"some":[54],"important":[55,125],"information":[56,126],"related":[57],"to":[58,62,98,109,121,128],"depression.":[59],"In":[60,96],"order":[61],"make":[63],"full":[64],"use":[65],"information,":[68],"this":[69],"paper":[70],"proposes":[71],"complex":[73,80],"squeeze-and-excitation":[74,104],"network":[75,106],"(CSENet)":[76],"The":[79],"used":[83],"as":[84],"feature,":[88,102],"contains":[90],"both":[91],"and":[93,138],"spectrogram.":[95],"addition,":[97],"acquire":[99],"discriminative":[101],"residual":[105],"employed":[108],"extract":[110],"deep":[111],"feature.":[113],"Finally,":[114],"attentive":[116],"temporal":[117],"pooling":[118],"utilized":[120],"dynamically":[122],"select":[123],"more":[124],"according":[127],"attention":[130],"mechanisms.":[131],"Experimental":[132],"results":[133],"AVEC":[136,139,159],"2013":[137],"2014":[140],"datasets":[141],"prove":[142],"effectiveness":[144],"our":[146,161],"proposed":[147,162],"method.":[148],"As":[149],"mean":[152],"absolute":[153],"error":[154],"(MAE)":[155],"evaluation":[156],"metric":[157],"2013,":[160],"method":[163],"acquires":[164],"state-of-the-art":[165],"performance.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
