{"id":"https://openalex.org/W3162130492","doi":"https://doi.org/10.1109/icassp39728.2021.9413988","title":"Analysing Bias in Spoken Language Assessment Using Concept Activation Vectors","display_name":"Analysing Bias in Spoken Language Assessment Using Concept Activation Vectors","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3162130492","doi":"https://doi.org/10.1109/icassp39728.2021.9413988","mag":"3162130492"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413988","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.17863/cam.65088","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078610427","display_name":"Xizi Wei","orcid":"https://orcid.org/0009-0001-4427-2951"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]},{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xizi Wei","raw_affiliation_strings":["Cambridge University Engineering Department, ALTA Institute, UK","School of Engineering, The University of Birmingham, UK"],"affiliations":[{"raw_affiliation_string":"Cambridge University Engineering Department, ALTA Institute, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"School of Engineering, The University of Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050766679","display_name":"Mark Gales","orcid":"https://orcid.org/0000-0002-5311-8219"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark J.F. Gales","raw_affiliation_strings":["Cambridge University Engineering Department, ALTA Institute, UK"],"affiliations":[{"raw_affiliation_string":"Cambridge University Engineering Department, ALTA Institute, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111076409","display_name":"Kate Knill","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kate M. Knill","raw_affiliation_strings":["Cambridge University Engineering Department, ALTA Institute, UK"],"affiliations":[{"raw_affiliation_string":"Cambridge University Engineering Department, ALTA Institute, UK","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078610427"],"corresponding_institution_ids":["https://openalex.org/I241749","https://openalex.org/I79619799"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62361837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7753","last_page":"7757"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9854999780654907,"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/T10028","display_name":"Topic Modeling","score":0.9854999780654907,"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/T10320","display_name":"Neural Networks and Applications","score":0.980400025844574,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9796000123023987,"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/computer-science","display_name":"Computer science","score":0.7193439602851868},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5524281859397888},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5401363372802734},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4946293532848358},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.4668263792991638},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4569580554962158},{"id":"https://openalex.org/keywords/inductive-bias","display_name":"Inductive bias","score":0.44888558983802795},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.41625961661338806},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.20759302377700806}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193439602851868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5524281859397888},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5401363372802734},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4946293532848358},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.4668263792991638},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4569580554962158},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.44888558983802795},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41625961661338806},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.20759302377700806},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413988","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:www.repository.cam.ac.uk:1810/317972","is_oa":false,"landing_page_url":"https://www.repository.cam.ac.uk/handle/1810/317972","pdf_url":null,"source":{"id":"https://openalex.org/S4306401777","display_name":"Apollo (University of Cambridge)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I241749","host_organization_name":"University of Cambridge","host_organization_lineage":["https://openalex.org/I241749"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Object"},{"id":"doi:10.17863/cam.65088","is_oa":true,"landing_page_url":"https://doi.org/10.17863/cam.65088","pdf_url":null,"source":{"id":"https://openalex.org/S7407050737","display_name":"Apollo","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.17863/cam.65088","is_oa":true,"landing_page_url":"https://doi.org/10.17863/cam.65088","pdf_url":null,"source":{"id":"https://openalex.org/S7407050737","display_name":"Apollo","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.8600000143051147,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1978642336","https://openalex.org/W2483215953","https://openalex.org/W2516809705","https://openalex.org/W2529194139","https://openalex.org/W2597603852","https://openalex.org/W2728567418","https://openalex.org/W2739575494","https://openalex.org/W2891613731","https://openalex.org/W2939437245","https://openalex.org/W2950018712","https://openalex.org/W2950113871","https://openalex.org/W2962059918","https://openalex.org/W2963238274","https://openalex.org/W2963483561","https://openalex.org/W2963749936","https://openalex.org/W2974482336","https://openalex.org/W3096582851","https://openalex.org/W4294029935","https://openalex.org/W4301785137","https://openalex.org/W6721933647","https://openalex.org/W6728271538","https://openalex.org/W6730042731","https://openalex.org/W6735632633","https://openalex.org/W6740019793","https://openalex.org/W6750391026","https://openalex.org/W6763681302"],"related_works":["https://openalex.org/W1810370127","https://openalex.org/W2064165679","https://openalex.org/W1588461101","https://openalex.org/W3208525924","https://openalex.org/W2885058781","https://openalex.org/W1594946127","https://openalex.org/W1552490082","https://openalex.org/W2189583758","https://openalex.org/W3009904625","https://openalex.org/W1983121850"],"abstract_inverted_index":{"A":[0,182],"significant":[1],"concern":[2],"with":[3,80],"deep":[4],"learning":[5],"based":[6],"approaches":[7],"is":[8,54,82,124,161],"that":[9,88,138],"they":[10],"are":[11],"difficult":[12],"to":[13,32,49,63,117,131,135,148,151,158,176],"interpret,":[14],"which":[15,177],"means":[16],"detecting":[17],"bias":[18,65,91,123,160,178,184,194],"in":[19,66,92,196],"network":[20,53],"predictions":[21],"can":[22,89],"be":[23,140,149],"challenging.":[24],"Concept":[25],"Activation":[26],"Vectors":[27],"(CAVs)":[28],"have":[29],"been":[30],"proposed":[31],"address":[33],"this":[34],"problem.":[35],"These":[36],"use":[37],"representations":[38],"-":[39,45],"perturbations":[40],"of":[41,46,77,86,113,122,141,156],"activation":[42],"function":[43],"outputs":[44],"interpretable":[47],"concepts":[48,87,137],"analyse":[50],"how":[51],"the":[52,57,78,83,106,132,164,189,193],"influenced":[55],"by":[56,186],"concept.":[58],"This":[59,126],"work":[60],"applies":[61],"CAVs":[62,129,157,187],"assess":[64,152],"a":[67,73,144,170,174],"spoken":[68],"language":[69],"assessment":[70],"(SLA)":[71],"system,":[72],"regression":[74],"task.":[75],"One":[76],"challenges":[79],"SLA":[81],"wide":[84],"range":[85],"introduce":[90],"training":[93,133,190],"data,":[94],"for":[95,119],"example":[96],"L1,":[97],"age,":[98],"acoustic":[99],"conditions,":[100],"and":[101,173],"particular":[102],"human":[103],"graders,":[104],"or":[105],"grading":[107],"instructions.":[108],"Simply":[109],"generating":[110],"large":[111],"quantities":[112],"expert":[114,197],"marked":[115,198],"data":[116,134,191],"check":[118],"all":[120],"forms":[121],"impractical.":[125],"paper":[127],"uses":[128],"applied":[130],"identify":[136],"might":[139],"concern,":[142],"allowing":[143],"more":[145],"targeted":[146],"dataset":[147],"collected":[150],"bias.":[153],"The":[154],"ability":[155],"detect":[159],"assessed":[162],"on":[163,188],"BULATS":[165],"speaking":[166],"test":[167,200],"using":[168],"both":[169],"standard":[171],"system":[172,175],"was":[179],"artificially":[180],"introduced.":[181],"strong":[183],"identified":[185],"matches":[192],"observed":[195],"held-out":[199],"data.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}
