{"id":"https://openalex.org/W3095789936","doi":"https://doi.org/10.21437/interspeech.2020-3005","title":"Removing Bias with Residual Mixture of Multi-View Attention for Speech Emotion Recognition","display_name":"Removing Bias with Residual Mixture of Multi-View Attention for Speech Emotion Recognition","publication_year":2020,"publication_date":"2020-10-25","ids":{"openalex":"https://openalex.org/W3095789936","doi":"https://doi.org/10.21437/interspeech.2020-3005","mag":"3095789936"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2020-3005","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","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/A5113981675","display_name":"Md Asif Jalal","orcid":null},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Md. Asif Jalal","raw_affiliation_strings":["Speech and Hearing Group (SPandH), The University of Sheffield"],"affiliations":[{"raw_affiliation_string":"Speech and Hearing Group (SPandH), The University of Sheffield","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078789113","display_name":"Rosanna Milner","orcid":"https://orcid.org/0000-0001-8924-0593"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rosanna Milner","raw_affiliation_strings":["Speech and Hearing Group (SPandH), The University of Sheffield"],"affiliations":[{"raw_affiliation_string":"Speech and Hearing Group (SPandH), The University of Sheffield","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030528300","display_name":"Thomas Hain","orcid":"https://orcid.org/0000-0003-0939-3464"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Thomas Hain","raw_affiliation_strings":["Speech and Hearing Group (SPandH), The University of Sheffield"],"affiliations":[{"raw_affiliation_string":"Speech and Hearing Group (SPandH), The University of Sheffield","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033198799","display_name":"Roger K. Moore","orcid":"https://orcid.org/0000-0003-0065-3311"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Roger K. Moore","raw_affiliation_strings":["Speech and Hearing Group (SPandH), The University of Sheffield"],"affiliations":[{"raw_affiliation_string":"Speech and Hearing Group (SPandH), The University of Sheffield","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113981675"],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":null,"apc_paid":null,"fwci":1.6113,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8442236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4084","last_page":"4088"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9986000061035156,"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/residual","display_name":"Residual","score":0.6996890306472778},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6971052885055542},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6709654331207275},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6299355626106262},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38345324993133545},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.34024345874786377},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2572556138038635},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1232157051563263}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6996890306472778},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6971052885055542},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6709654331207275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6299355626106262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38345324993133545},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.34024345874786377},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2572556138038635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1232157051563263}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2020-3005","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-3005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:171417","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1509274023","https://openalex.org/W1522301498","https://openalex.org/W1531333757","https://openalex.org/W1974470404","https://openalex.org/W2026984028","https://openalex.org/W2055911634","https://openalex.org/W2110052520","https://openalex.org/W2111926505","https://openalex.org/W2125610823","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2146334809","https://openalex.org/W2239141610","https://openalex.org/W2409534643","https://openalex.org/W2625297138","https://openalex.org/W2747664154","https://openalex.org/W2765720631","https://openalex.org/W2765998482","https://openalex.org/W2888869035","https://openalex.org/W2889374687","https://openalex.org/W2899366898","https://openalex.org/W2936113082","https://openalex.org/W2963403868","https://openalex.org/W2963495494","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2972498864","https://openalex.org/W2972811324","https://openalex.org/W2972965453","https://openalex.org/W3007558004","https://openalex.org/W3008554267","https://openalex.org/W4239447739","https://openalex.org/W4297786033","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2498789492","https://openalex.org/W2521347458","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2925692864","https://openalex.org/W3126677997","https://openalex.org/W1610857240"],"abstract_inverted_index":{"Speech":[0],"emotion":[1,24,41,116],"recognition":[2,25],"is":[3,31,73,97,123,154],"essential":[4],"for":[5,88,114],"obtaining":[6],"emotional":[7],"intelligence":[8],"which":[9,35],"affects":[10],"the":[11,40,120,139,157,164,176],"understanding":[12],"of":[13,17,22,57,79,119,129,147],"context":[14,70,89],"and":[15,47,83,91,106,109,167],"meaning":[16],"speech.":[18,61],"The":[19,75,95],"fundamental":[20],"challenges":[21],"speech":[23,115],"from":[26],"a":[27,65,126,133],"machine":[28],"learning":[29,92],"standpoint":[30],"to":[32,48,54,99,102,174],"extract":[33],"patterns":[34],"carry":[36],"maximum":[37],"correlation":[38],"with":[39,125,163],"information":[42,58],"encoded":[43],"in":[44,104,132],"this":[45,63],"signal,":[46],"be":[49,100],"as":[50,52],"insensitive":[51],"possible":[53],"other":[55,107],"types":[56],"carried":[59],"by":[60],"In":[62],"paper,":[64],"novel":[66],"recurrent":[67],"residual":[68],"temporal":[69],"modelling":[71],"framework":[72,76,96],"proposed.":[74],"includes":[77],"mixture":[78],"multi-view":[80],"attention":[81,158,172],"smoothing":[82],"high":[84],"dimensional":[85],"feature":[86,93],"projection":[87],"expansion":[90],"representations.":[94],"designed":[98],"robust":[101],"changes":[103],"speaker":[105],"distortions,":[108],"it":[110],"provides":[111],"state-of-the-art":[112,152],"results":[113],"recognition.":[117],"Performance":[118],"proposed":[121],"approach":[122],"compared":[124],"wide":[127],"range":[128],"current":[130],"architectures":[131],"standard":[134],"4-class":[135],"classification":[136],"task":[137],"on":[138],"widely":[140],"used":[141],"IEMOCAP":[142],"corpus.":[143],"A":[144],"significant":[145],"improvement":[146],"4%":[148],"unweighted":[149],"accuracy":[150],"over":[151],"systems":[153],"observed.":[155],"Additionally,":[156],"vectors":[159],"have":[160],"been":[161],"aligned":[162],"input":[165],"segments":[166],"plotted":[168],"at":[169],"two":[170],"different":[171],"levels":[173],"demonstrate":[175],"effectiveness.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}
