{"id":"https://openalex.org/W7157627456","doi":"https://doi.org/10.48550/arxiv.2604.24770","title":"Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR","display_name":"Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7157627456","doi":"https://doi.org/10.48550/arxiv.2604.24770"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24770","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24770","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.24770","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033681555","display_name":"Minsik Lee","orcid":"https://orcid.org/0000-0003-4941-4311"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lee, Minsik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134848769","display_name":"Seoi Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Seoi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134854595","display_name":"Chongmin Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Chongmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101599425","display_name":"Sieun Choi","orcid":"https://orcid.org/0009-0003-9638-6680"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Sieun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134835524","display_name":"Jian Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134854517","display_name":"Jua Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5080664764","display_name":"Jihie Kim","orcid":"https://orcid.org/0000-0003-2358-4021"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jihie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5033681555"],"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":0.961899995803833,"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":0.961899995803833,"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/T10863","display_name":"Voice and Speech Disorders","score":0.008299999870359898,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.006399999838322401,"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/pipeline","display_name":"Pipeline (software)","score":0.7200000286102295},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.512499988079071},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4580000042915344},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4447000026702881},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.42980000376701355},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.39809998869895935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.722000002861023},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7200000286102295},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5001000165939331},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4447000026702881},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41679999232292175},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C43617652","wikidata":"https://www.wikidata.org/wiki/Q7575399","display_name":"Speech production","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C155635449","wikidata":"https://www.wikidata.org/wiki/Q4674699","display_name":"Acoustic model","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24770","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24770","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.24770","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24770","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":"article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6712912321090698}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"recent":[1],"progress":[2],"in":[3,35,109,144],"automatic":[4],"speech":[5,57,76,118],"recognition":[6],"(ASR),":[7],"elderly":[8,26,56,78,117],"ASR":[9],"(EASR)":[10],"remains":[11],"challenging":[12],"due":[13],"to":[14,92,140],"limited":[15],"training":[16],"data":[17,33,39,91],"and":[18,22,69,106,115,124],"the":[19,59,66,70,89,101,128,151],"distinct":[20],"acoustic":[21],"linguistic":[23],"characteristics":[24],"of":[25,65,103],"speech.":[27],"In":[28],"this":[29],"work,":[30],"we":[31],"address":[32],"scarcity":[34],"EASR":[36],"through":[37],"a":[38,141],"augmentation":[40,104,136],"pipeline":[41],"that":[42,127],"combines":[43],"large":[44],"language":[45],"model":[46,72],"(LLM)-based":[47],"transcript":[48],"paraphrasing":[49],"with":[50,88,150],"text-to-speech":[51],"(TTS)":[52],"synthesis.":[53],"Given":[54],"an":[55],"dataset,":[58],"LLM":[60],"first":[61],"generates":[62],"elderly-contextual":[63],"paraphrases":[64],"original":[67,90],"transcripts,":[68],"TTS":[71],"then":[73],"synthesizes":[74],"corresponding":[75],"using":[77],"reference":[79],"speakers.":[80],"The":[81],"resulting":[82],"synthetic":[83],"audio-text":[84],"pairs":[85],"are":[86],"merged":[87],"fine-tune":[93],"Whisper":[94,152],"without":[95],"architectural":[96],"modification.":[97],"We":[98],"further":[99],"analyze":[100],"effects":[102],"ratio":[105],"reference-speaker":[107],"composition":[108],"low-resource":[110],"EASR.":[111],"Experiments":[112],"on":[113],"English":[114],"Korean":[116],"datasets":[119],"from":[120],"speakers":[121],"aged":[122],"70":[123],"above":[125],"show":[126],"proposed":[129],"method":[130],"consistently":[131],"improves":[132],"performance":[133],"over":[134],"conventional":[135],"baselines,":[137],"achieving":[138],"up":[139],"58.2%":[142],"reduction":[143],"word":[145],"error":[146],"rate":[147],"(WER)":[148],"compared":[149],"baseline.":[153]},"counts_by_year":[],"updated_date":"2026-04-30T06:11:10.768123","created_date":"2026-04-30T00:00:00"}