{"id":"https://openalex.org/W7214076571","doi":"https://doi.org/10.48550/arxiv.2609.25471","title":"A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization","display_name":"A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization","publication_year":2026,"publication_date":"2026-09-21","ids":{"openalex":"https://openalex.org/W7214076571","doi":"https://doi.org/10.48550/arxiv.2609.25471"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.25471","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25471","pdf_url":"https://arxiv.org/pdf/2609.25471","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.25471","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039562436","display_name":"Wonho Bae","orcid":"https://orcid.org/0000-0002-6678-5299","observed_orcids":["https://orcid.org/0000-0002-6678-5299"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bae, Wonho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090927958","display_name":"Zakaria Aldeneh","orcid":"https://orcid.org/0000-0003-4599-2448","observed_orcids":["https://orcid.org/0000-0003-4599-2448"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aldeneh, Zakaria","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031363335","display_name":"Martin Pelik\u00e1n","orcid":"https://orcid.org/0009-0003-4101-5575","observed_orcids":["https://orcid.org/0009-0003-4101-5575"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pelikan, Martin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022347882","display_name":"Jan Silovsk\u00fd","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silovsky, Jan \"Honza\"","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106542588","display_name":"Tatiana Likhomanenko","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Likhomanenko, Tatiana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017461331","display_name":"Sheikh Shams Azam","orcid":"https://orcid.org/0000-0001-7678-5092","observed_orcids":["https://orcid.org/0000-0001-7678-5092"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Azam, Sheikh Shams","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":true,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8032000064849854,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.8032000064849854,"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":0.13729999959468842,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.029400000348687172,"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/federated-semi-supervised-learning","display_name":"semi-supervised federated learning","score":0.9959999918937683},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"speech recognition","score":0.843999981880188},{"id":"https://openalex.org/keywords/pseudo-labeling","display_name":"pseudo-labeling","score":0.9020000100135803},{"id":"https://openalex.org/keywords/domain-shift","display_name":"domain shift","score":0.8830000162124634},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.7089999914169312},{"id":"https://openalex.org/keywords/batch-size","display_name":"batch size","score":0.7390000224113464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067000269889832},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.5586000084877014},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5396000146865845},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.49939998984336853},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3855000138282776},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C177562468","wikidata":"https://www.wikidata.org/wiki/Q182893","display_name":"Dispersion (optics)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C164554305","wikidata":"https://www.wikidata.org/wiki/Q71550","display_name":"Application server","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C2779955035","wikidata":"https://www.wikidata.org/wiki/Q4686785","display_name":"Advice (programming)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.25290000438690186},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.25471","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25471","pdf_url":"https://arxiv.org/pdf/2609.25471","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.25471","doi":"https://doi.org/10.48550/arxiv.2609.25471","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.25471","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.25471","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25471","pdf_url":"https://arxiv.org/pdf/2609.25471","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214076571.pdf","grobid_xml":"https://content.openalex.org/works/W7214076571.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W1828163288","https://openalex.org/W4318146637","https://openalex.org/W4321854172","https://openalex.org/W4379744962","https://openalex.org/W4403573600","https://openalex.org/W4403653931","https://openalex.org/W4408353632","https://openalex.org/W4415101218","https://openalex.org/W7131893892","https://openalex.org/W7134249032"],"related_works":["https://openalex.org/W4281972165","https://openalex.org/W4391021524","https://openalex.org/W4297841396","https://openalex.org/W4303495611","https://openalex.org/W4403007049","https://openalex.org/W4386712571","https://openalex.org/W4409196535","https://openalex.org/W4283324956","https://openalex.org/W3163004056","https://openalex.org/W7133230604"],"abstract_inverted_index":{"Semi-supervised":[0],"federated":[1],"learning":[2],"(SSFL)":[3],"trains":[4],"models":[5],"on":[6,22,60,79,99,161,259,266],"clients'":[7],"unlabeled":[8],"data":[9,81,163,204,237],"using":[10],"a":[11,17,47,89,118,139],"teacher":[12,67,87,92,112,141,170,189],"to":[13,50,203,275],"generate":[14],"pseudo-labels,":[15],"with":[16,241],"small":[18],"labeled":[19,80,162],"seed":[20,130,179,236],"dataset":[21],"the":[23,37,66,71,74,86,109,129,134,153,156,168,178,195,210,220,232,235,255,273],"server.":[24],"Automatic":[25],"Speech":[26],"Recognition":[27],"(ASR)":[28],"is":[29,200,226,228],"particularly":[30],"fragile":[31],"here:":[32],"pseudo-label":[33],"errors":[34],"compound":[35],"across":[36,41],"output":[38],"sequence":[39],"and":[40,73,123,133,173,206,217,238,269],"training":[42,160],"rounds":[43,165],"into":[44],"divergence,":[45],"leaving":[46],"large":[48],"gap":[49,58,274],"fully-supervised":[51,276],"FL.":[52,277],"We":[53],"show":[54],"that":[55,82,212],"closing":[56],"this":[57,174],"turns":[59],"two":[61,184],"coupled":[62],"design":[63],"axes":[64,185],"--":[65,120,166,172,209],"(which":[68],"model":[69],"generates":[70],"pseudo-labels)":[72],"anchor":[75,154,196],"(the":[76],"server-side":[77],"updates":[78],"stabilize":[83],"training).":[84],"On":[85,152],"axis,":[88,155],"per-client":[90],"online":[91,135,144,169],"(each":[93],"client's":[94],"own":[95],"evolving":[96],"model)":[97],"diverges":[98],"its":[100,239],"own,":[101],"but":[102],"once":[103,194],"stabilized":[104],"it":[105],"matches":[106,148],"or":[107,149],"beats":[108,150],"broadcast":[110],"global":[111],"(one":[113],"server":[114,157,221],"model,":[115,180],"fixed":[116],"within":[117],"round)":[119],"decisively":[121],"in-domain":[122,268],"competitively":[124],"under":[125],"domain":[126],"shift.":[127],"As":[128],"grows":[131],"stronger":[132],"teacher's":[136],"advantage":[137],"narrows,":[138],"transitioning":[140],"(global":[142],"$\\rightarrow$":[143],"at":[145],"round":[146],"$r$)":[147],"both.":[151],"must":[158],"keep":[159],"between":[164],"otherwise":[167],"drifts":[171],"interleaving,":[175],"more":[176],"than":[177],"governs":[181],"convergence.":[182],"The":[183],"are":[186],"inseparable:":[187],"aggressive":[188],"choices":[190],"pay":[191],"off":[192],"only":[193],"stabilizes":[197],"training,":[198,252],"which":[199],"highly":[201],"sensitive":[202],"augmentation":[205],"batch":[207],"size":[208],"settings":[211],"govern":[213],"how":[214],"much":[215,224],"input":[216],"gradient":[218],"noise":[219],"injects.":[222],"How":[223],"stabilization":[225],"needed":[227],"domain-dependent,":[229],"governed":[230],"by":[231,264],"dispersion":[233],"of":[234,261],"overlap":[240],"client":[242],"data.":[243],"These":[244],"findings":[245],"yield":[246],"guidelines":[247],"for":[248],"SSFL":[249],"in":[250],"ASR":[251],"improving":[253],"over":[254],"strongest":[256],"prior":[257],"method":[258],"9":[260],"11":[262],"pairs,":[263],"$20.8\\%$":[265],"average":[267],"$10.0\\%$":[270],"cross-domain,":[271],"narrowing":[272]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-24T00:00:00"}