{"id":"https://openalex.org/W7220858363","doi":"https://doi.org/10.1109/ictiia70925.2026.11717155","title":"Speech Emotion Recognition Beyond Benchmarks: Robustness, Efficiency, and Evaluation for Real-World Deployment","display_name":"Speech Emotion Recognition Beyond Benchmarks: Robustness, Efficiency, and Evaluation for Real-World Deployment","publication_year":2026,"publication_date":"2026-09-01","ids":{"openalex":"https://openalex.org/W7220858363","doi":"https://doi.org/10.1109/ictiia70925.2026.11717155"},"language":"en","primary_location":{"id":"doi:10.1109/ictiia70925.2026.11717155","doi":"https://doi.org/10.1109/ictiia70925.2026.11717155","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ictiia70925.2026.11717155","pdf_url":null,"source":{"id":"https://openalex.org/S7407089228","display_name":"International Conference on Technology Innovation and Its Applications (ICTIIA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 3rd International Conference on Technology Innovation and Its Applications (ICTIIA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/ictiia70925.2026.11717155","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126592111","display_name":"Dominik Beyer","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Beyer","raw_affiliation_strings":["FZI Research Center for Information Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043713041","display_name":"Florian Mazura","orcid":"https://orcid.org/0009-0008-0935-2703","observed_orcids":["https://orcid.org/0009-0008-0935-2703"]},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Mazura","raw_affiliation_strings":["FZI Research Center for Information Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5157881273","display_name":"Julian K\u00f6der","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Julian K\u00f6der","raw_affiliation_strings":["FZI Research Center for Information Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067846212","display_name":"Wilhelm Stork","orcid":"https://orcid.org/0000-0003-0579-4615","observed_orcids":["https://orcid.org/0000-0003-0579-4615"]},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wilhelm Stork","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9916999936103821,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9916999936103821,"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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.007199999876320362,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.0005000000237487257,"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/speech-emotion-recognition","display_name":"speech emotion recognition","score":0.9959999918937683},{"id":"https://openalex.org/keywords/robustness","display_name":"robustness","score":0.7400000095367432},{"id":"https://openalex.org/keywords/edge-deployment","display_name":"edge deployment","score":0.7390000224113464},{"id":"https://openalex.org/keywords/cross-corpus-generalization","display_name":"cross-corpus generalization","score":0.7260000109672546},{"id":"https://openalex.org/keywords/iemocap","display_name":"IEMOCAP","score":0.7360000014305115},{"id":"https://openalex.org/keywords/wav2vec-2-0","display_name":"wav2vec 2.0","score":0.875},{"id":"https://openalex.org/keywords/wavlm","display_name":"WavLM","score":0.8939999938011169},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.4580000042915344},{"id":"https://openalex.org/keywords/smartphone-recordings","display_name":"smartphone recordings","score":0.718999981880188},{"id":"https://openalex.org/keywords/evaluation-protocol","display_name":"evaluation protocol","score":0.4309999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.550000011920929},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.49549999833106995},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.40380001068115234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.30390000343322754},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictiia70925.2026.11717155","doi":"https://doi.org/10.1109/ictiia70925.2026.11717155","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ictiia70925.2026.11717155","pdf_url":null,"source":{"id":"https://openalex.org/S7407089228","display_name":"International Conference on Technology Innovation and Its Applications (ICTIIA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 3rd International Conference on Technology Innovation and Its Applications (ICTIIA)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/ictiia70925.2026.11717155","doi":"https://doi.org/10.1109/ictiia70925.2026.11717155","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ictiia70925.2026.11717155","pdf_url":null,"source":{"id":"https://openalex.org/S7407089228","display_name":"International Conference on Technology Innovation and Its Applications (ICTIIA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 3rd International Conference on Technology Innovation and Its Applications (ICTIIA)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W175750906","https://openalex.org/W1501669607","https://openalex.org/W1966797434","https://openalex.org/W2030931454","https://openalex.org/W2146334809","https://openalex.org/W2170505850","https://openalex.org/W2972602947","https://openalex.org/W3084484668","https://openalex.org/W3169320628","https://openalex.org/W3209984917","https://openalex.org/W4225635674","https://openalex.org/W4286905321","https://openalex.org/W4383551941","https://openalex.org/W4387055738","https://openalex.org/W4388103902","https://openalex.org/W4389222634","https://openalex.org/W4392931772","https://openalex.org/W4393028299","https://openalex.org/W4393522565","https://openalex.org/W4401110706","https://openalex.org/W4402111801","https://openalex.org/W4403340362","https://openalex.org/W4407801326","https://openalex.org/W4409058640","https://openalex.org/W4409209942","https://openalex.org/W4409388791","https://openalex.org/W4415432908"],"related_works":["https://openalex.org/W7166821856","https://openalex.org/W2791925433","https://openalex.org/W7214628422","https://openalex.org/W3047908379","https://openalex.org/W7117658666","https://openalex.org/W7220682064","https://openalex.org/W2399125226","https://openalex.org/W7117783447","https://openalex.org/W2747664154","https://openalex.org/W4377231298"],"abstract_inverted_index":{"Robust":[0],"Speech":[1],"Emotion":[2],"Recognition":[3],"(SER)":[4],"for":[5,111,121,134],"edge":[6],"applications":[7],"requires":[8],"evidence":[9],"beyond":[10],"within-corpus":[11],"accuracy.":[12],"We":[13],"propose":[14],"a":[15,26,43],"three-tier":[16],"protocol":[17,117],"separating":[18],"speaker,":[19],"corpus,":[20],"and":[21,40,93,113,125],"deployment-proxy":[22],"shifts":[23],"rather":[24],"than":[25],"new":[27],"classifier.":[28],"It":[29],"compares":[30],"Wav2Vec":[31],"2.0":[32],"Base,":[33,35,37],"WavLM":[34],"Whisper":[36,38,63,91],"Tiny,":[39],"ReDimNet-B2":[41,94],"on":[42,51,60,68,89],"five-corpus":[44],"composite":[45],"training":[46],"set.":[47],"Models":[48],"are":[49],"selected":[50],"speaker-independent":[52],"validation":[53],"with":[54],"unseen":[55,61],"source-corpus":[56],"speakers,":[57],"then":[58],"tested":[59,67],"IEMOCAP.":[62,90],"Tiny":[64,92],"is":[65,130],"also":[66],"108":[69],"smartphone":[70,106],"recordings":[71],"by":[72],"9":[73],"non-professional":[74],"speakers.":[75],"Speaker-independent":[76],"UAR":[77],"ranges":[78],"from":[79],"0.752":[80],"to":[81,85,87,97],"0.786":[82],"but":[83],"falls":[84],"0.475":[86],"0.531":[88],"remain":[95],"close":[96],"larger":[98],"Base":[99],"models":[100,124],"despite":[101],"smaller":[102],"encoders,":[103],"while":[104],"the":[105],"test":[107],"reveals":[108],"class-dependent":[109],"failures":[110],"happy":[112],"angry":[114],"speech.":[115],"The":[116],"structures":[118],"stress":[119],"testing":[120],"compact":[122],"SER":[123],"shows":[126],"parameter":[127],"count":[128],"alone":[129],"an":[131],"insufficient":[132],"proxy":[133],"robustness":[135],"or":[136],"deployability.":[137]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-08T00:00:00"}
