{"id":"https://openalex.org/W3115394420","doi":"https://doi.org/10.1109/access.2020.3047395","title":"Attention-Based Convolution Skip Bidirectional Long Short-Term Memory Network for Speech Emotion Recognition","display_name":"Attention-Based Convolution Skip Bidirectional Long Short-Term Memory Network for Speech Emotion Recognition","publication_year":2020,"publication_date":"2020-12-25","ids":{"openalex":"https://openalex.org/W3115394420","doi":"https://doi.org/10.1109/access.2020.3047395","mag":"3115394420"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3047395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047395","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09308936.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://ieeexplore.ieee.org/ielx7/6287639/9312710/09308936.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107700888","display_name":"Huiyun Zhang","orcid":"https://orcid.org/0000-0001-9672-1539"},"institutions":[{"id":"https://openalex.org/I20616075","display_name":"Qinghai Normal University","ror":"https://ror.org/03az1t892","country_code":"CN","type":"education","lineage":["https://openalex.org/I20616075"]},{"id":"https://openalex.org/I4210121080","display_name":"Qinghai Tibetan Hospital","ror":"https://ror.org/03mmka096","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210121080"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyun Zhang","raw_affiliation_strings":["Key Laboratory of Tibetan Information Processing, Ministry of Education, Xining, China","School of Computer Science, Qinghai Normal University, Xining, China","Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Xining, China"],"raw_orcid":"https://orcid.org/0000-0001-9672-1539","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tibetan Information Processing, Ministry of Education, Xining, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Qinghai Normal University, Xining, China","institution_ids":["https://openalex.org/I20616075"]},{"raw_affiliation_string":"Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Xining, China","institution_ids":["https://openalex.org/I4210121080"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Heming Huang","orcid":"https://orcid.org/0000-0003-2735-4792"},"institutions":[{"id":"https://openalex.org/I20616075","display_name":"Qinghai Normal University","ror":"https://ror.org/03az1t892","country_code":"CN","type":"education","lineage":["https://openalex.org/I20616075"]},{"id":"https://openalex.org/I4210121080","display_name":"Qinghai Tibetan Hospital","ror":"https://ror.org/03mmka096","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210121080"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heming Huang","raw_affiliation_strings":["Key Laboratory of Tibetan Information Processing, Ministry of Education, Xining, China","School of Computer Science, Qinghai Normal University, Xining, China","Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Xining, China"],"raw_orcid":"https://orcid.org/0000-0003-2735-4792","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tibetan Information Processing, Ministry of Education, Xining, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Qinghai Normal University, Xining, China","institution_ids":["https://openalex.org/I20616075"]},{"raw_affiliation_string":"Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Xining, China","institution_ids":["https://openalex.org/I4210121080"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087988017","display_name":"Henry Han","orcid":"https://orcid.org/0000-0003-0273-6719"},"institutions":[{"id":"https://openalex.org/I164389053","display_name":"Fordham University","ror":"https://ror.org/03qnxaf80","country_code":"US","type":"education","lineage":["https://openalex.org/I164389053"]},{"id":"https://openalex.org/I20616075","display_name":"Qinghai Normal University","ror":"https://ror.org/03az1t892","country_code":"CN","type":"education","lineage":["https://openalex.org/I20616075"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Henry Han","raw_affiliation_strings":["Department of Computer and Information Science, Fordham University, New York City, NY, USA","School of Computer Science, Qinghai Normal University, Xining, China"],"raw_orcid":"https://orcid.org/0000-0003-0273-6719","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Fordham University, New York City, NY, USA","institution_ids":["https://openalex.org/I164389053"]},{"raw_affiliation_string":"School of Computer Science, Qinghai Normal University, Xining, China","institution_ids":["https://openalex.org/I20616075"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.6822,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.90300618,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"5332","last_page":"5342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"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":0.9983000159263611,"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/computer-science","display_name":"Computer science","score":0.84294593334198},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7330511808395386},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7044709324836731},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6637197732925415},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6276026964187622},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5861911773681641},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5345145463943481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4859858453273773},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4588814675807953},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4180390238761902},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3504978120326996},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.1999066174030304},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18664053082466125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.84294593334198},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7330511808395386},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7044709324836731},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6637197732925415},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6276026964187622},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5861911773681641},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5345145463943481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4859858453273773},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4588814675807953},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4180390238761902},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3504978120326996},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.1999066174030304},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18664053082466125},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3047395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047395","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09308936.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1daf24bcc12e4c2b89fa6be079a35f76","is_oa":true,"landing_page_url":"https://doaj.org/article/1daf24bcc12e4c2b89fa6be079a35f76","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 9, Pp 5332-5342 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3047395","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047395","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09308936.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5899999737739563,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G31396423","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u8fc1\u79fb\u5b66\u4e60\u7684\u5b89\u591a\u85cf\u8bed\u8bed\u97f3\u8bc6\u522b\u7814\u7a76","funder_award_id":"62066039","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3115394420.pdf","grobid_xml":"https://content.openalex.org/works/W3115394420.grobid-xml"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W1576808190","https://openalex.org/W1594352493","https://openalex.org/W1972280480","https://openalex.org/W1972292025","https://openalex.org/W1972323525","https://openalex.org/W1975205701","https://openalex.org/W1989639247","https://openalex.org/W2006912121","https://openalex.org/W2038821742","https://openalex.org/W2052020713","https://openalex.org/W2070823712","https://openalex.org/W2070855231","https://openalex.org/W2087618018","https://openalex.org/W2092718714","https://openalex.org/W2099767163","https://openalex.org/W2103108187","https://openalex.org/W2103412248","https://openalex.org/W2111479516","https://openalex.org/W2111926505","https://openalex.org/W2128005861","https://openalex.org/W2141853407","https://openalex.org/W2158514474","https://openalex.org/W2280340421","https://openalex.org/W2488508821","https://openalex.org/W2579665659","https://openalex.org/W2589599921","https://openalex.org/W2592702372","https://openalex.org/W2611029437","https://openalex.org/W2613769592","https://openalex.org/W2614874155","https://openalex.org/W2625297138","https://openalex.org/W2707551695","https://openalex.org/W2781964364","https://openalex.org/W2786779322","https://openalex.org/W2786857286","https://openalex.org/W2799331981","https://openalex.org/W2810490977","https://openalex.org/W2883496341","https://openalex.org/W2885005742","https://openalex.org/W2888170456","https://openalex.org/W2891588573","https://openalex.org/W2892370324","https://openalex.org/W2893146414","https://openalex.org/W2899578638","https://openalex.org/W2899840908","https://openalex.org/W2912939198","https://openalex.org/W2917572534","https://openalex.org/W2917987043","https://openalex.org/W2939488497","https://openalex.org/W2939764705","https://openalex.org/W2940259008","https://openalex.org/W2945108686","https://openalex.org/W2954046516","https://openalex.org/W2959133507","https://openalex.org/W2959546144","https://openalex.org/W2963697785","https://openalex.org/W2963698657","https://openalex.org/W2963929227","https://openalex.org/W2971275122","https://openalex.org/W2972731924","https://openalex.org/W2977809668","https://openalex.org/W2978714016","https://openalex.org/W2997648541","https://openalex.org/W2998295548","https://openalex.org/W2999296562","https://openalex.org/W3000516905","https://openalex.org/W3000894155","https://openalex.org/W3014475539","https://openalex.org/W3015476328","https://openalex.org/W3015906487","https://openalex.org/W3016243233","https://openalex.org/W3032305282","https://openalex.org/W3034339621","https://openalex.org/W3041751009","https://openalex.org/W3056919267","https://openalex.org/W3081425542","https://openalex.org/W3093863290","https://openalex.org/W3104904831","https://openalex.org/W6635725049","https://openalex.org/W6675284472","https://openalex.org/W6753267587"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W3103989898","https://openalex.org/W4287804464","https://openalex.org/W3168412960","https://openalex.org/W4210571422"],"abstract_inverted_index":{"Speech":[0],"emotion":[1,31],"recognition":[2,32],"is":[3,57,145],"a":[4,41],"challenging":[5],"task":[6],"in":[7,110],"natural":[8],"language":[9],"processing.":[10],"It":[11,63],"relies":[12],"heavily":[13],"on":[14],"the":[15,102,117,122,146],"effectiveness":[16],"of":[17,89,104,130],"speech":[18,30,61],"features":[19,95],"and":[20,82,92,107,120,132],"acoustic":[21,25,44],"models.":[22],"However,":[23],"existing":[24],"models":[26],"may":[27],"not":[28],"handle":[29],"efficiently":[33],"for":[34],"their":[35],"built-in":[36],"limitations.":[37],"In":[38,98],"this":[39,144],"work,":[40],"novel":[42],"deep-learning":[43],"model":[45,124],"called":[46],"attention-based":[47],"skip":[48,74],"convolution":[49],"bi-directional":[50],"long":[51],"short-term":[52],"memory,":[53],"abbreviated":[54],"as":[55,137],"SCBAMM,":[56],"proposed":[58,123],"to":[59,113],"recognize":[60],"emotion.":[62],"has":[64],"eight":[65],"hidden":[66],"layers,":[67,71],"namely,":[68],"two":[69],"dense":[70],"convolutional":[72],"layer,":[73,75,77,79,81],"mask":[76],"Bi-LSTM":[78],"attention":[80],"pooling":[83],"layer.":[84],"SCBAMM":[85,125],"makes":[86],"better":[87],"use":[88],"spatiotemporal":[90],"information":[91],"captures":[93],"emotion-related":[94],"more":[96],"effectively.":[97],"addition,":[99],"it":[100],"solves":[101],"problems":[103],"gradient":[105,108],"exploding":[106],"vanishing":[109],"deep":[111],"learning":[112],"some":[114],"extent.":[115],"On":[116],"databases":[118],"EMO-DB":[119],"CASIA,":[121],"achieves":[126],"an":[127],"accuracy":[128,148],"rate":[129],"94.58%":[131],"72.50%,":[133],"respectively.":[134],"As":[135],"far":[136],"we":[138],"know,":[139],"compared":[140],"with":[141],"peer":[142],"models,":[143],"best":[147],"rate.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
