{"id":"https://openalex.org/W7156111636","doi":"https://doi.org/10.48550/arxiv.2604.22631","title":"Identifying and typifying demographic unfairness in phoneme-level embeddings of self-supervised speech recognition models","display_name":"Identifying and typifying demographic unfairness in phoneme-level embeddings of self-supervised speech recognition models","publication_year":2026,"publication_date":"2026-04-24","ids":{"openalex":"https://openalex.org/W7156111636","doi":"https://doi.org/10.48550/arxiv.2604.22631"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.22631","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099096330","display_name":"Felix Herron","orcid":"https://orcid.org/0009-0005-9771-4994"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Herron, Felix","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134725290","display_name":"Solange Rossato","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rossato, Solange","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134723775","display_name":"Alexandre Allauzen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Allauzen, Alexandre","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134688736","display_name":"Fran\u00e7ois Portet","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Portet, Fran\u00e7ois","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9412999749183655,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9412999749183655,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.013299999758601189,"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/T11448","display_name":"Face recognition and analysis","score":0.0071000000461936,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/variance","display_name":"Variance (accounting)","score":0.5906999707221985},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5864999890327454},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.47110000252723694},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4284000098705292},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.3921000063419342},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.3797999918460846},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.366100013256073},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.2973000109195709}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6754999756813049},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5906999707221985},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5864999890327454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5670999884605408},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4284000098705292},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3880999982357025},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C100253034","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Systematic error","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C137584468","wikidata":"https://www.wikidata.org/wiki/Q35395","display_name":"Phonetics","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C40696583","wikidata":"https://www.wikidata.org/wiki/Q989120","display_name":"Type I and type II errors","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2743000090122223},{"id":"https://openalex.org/C2780623907","wikidata":"https://www.wikidata.org/wiki/Q106394435","display_name":"Disadvantaged","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.22631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5263546109199524}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"automatic":[1],"speech":[2,45],"recognition":[3],"(ASR)":[4],"systems":[5],"have":[6],"been":[7],"observed":[8],"to":[9,28,181],"function":[10],"better":[11],"for":[12,59,110,116,168],"certain":[13],"speaker":[14],"groups":[15],"(SGs)":[16],"than":[17,183],"others,":[18],"despite":[19],"recent":[20],"gains":[21],"in":[22,50,77,80,86,122,160,171],"overall":[23],"performance.":[24],"One":[25],"potential":[26],"impediment":[27],"progress":[29],"towards":[30],"fairer":[31],"ASR":[32,81],"is":[33,114,176],"a":[34,67,102,178,194],"more":[35],"nuanced":[36],"understanding":[37],"of":[38,41,57,72,119,138,156,206,215],"the":[39,52,55,117,126,142,204],"types":[40,71,155],"modeling":[42,78],"errors":[43],"that":[44,74,95,111,131,153,189],"encoder":[46,191],"models":[47,192],"make,":[48],"and":[49,61,133,163,199],"particular":[51],"difference":[53],"between":[54],"structure":[56],"embeddings":[58,162],"high-performance":[60],"low-performance":[62],"SGs.":[63],"This":[64],"paper":[65],"proposes":[66],"framework":[68],"typifying":[69],"two":[70],"error":[73,157,175],"can":[75],"occur":[76],"phonemes":[79],"systems:":[82],"random":[83,174,216],"error/high":[84],"variance":[85,140],"phoneme":[87,97,123,139,148,161,208],"embedding,":[88],"vs":[89],"systematic":[90,184],"error/embedding":[91],"bias.":[92],"We":[93,151],"find":[94,130,188],"training":[96],"classification":[98,209],"probes":[99],"only":[100],"on":[101],"single,":[103],"typically":[104],"disadvantaged":[105],"SG,":[106,112],"sometimes":[107],"improves":[108],"performance":[109],"which":[113],"evidence":[115],"existence":[118],"SG-level":[120,169],"bias":[121],"embeddings.":[124],"On":[125],"other":[127],"hand,":[128],"we":[129,187],"speakers":[132],"SGs":[134],"with":[135,146],"higher":[136],"levels":[137,214],"are":[141,158,165],"same":[143],"as":[144],"those":[145],"worse":[147],"prediction":[149],"accuracy.":[150],"conclude":[152],"both":[154,164],"present":[159],"candidate":[166],"causes":[167],"unfairness":[170],"ASR,":[172],"though":[173],"likely":[177],"greater":[179],"hindrance":[180],"fairness":[182],"error.":[185,218],"Furthermore,":[186],"finetuning":[190],"using":[193],"fairness-enhancing":[195],"algorithm":[196],"(domain":[197],"enhancing":[198],"adversarial":[200],"training)":[201],"changes":[202],"neither":[203],"benefits":[205],"in-domain":[207],"probe":[210],"training,":[211],"nor":[212],"measured":[213],"embedding":[217]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-28T00:00:00"}