{"id":"https://openalex.org/W7163878942","doi":"https://doi.org/10.48550/arxiv.2606.07259","title":"Assessing True Generalisability of Audio-Visual Speech Recognisers","display_name":"Assessing True Generalisability of Audio-Visual Speech Recognisers","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163878942","doi":"https://doi.org/10.48550/arxiv.2606.07259"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07259","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07259","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,"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.2606.07259","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114119810","display_name":"Zhaofeng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Zhaofeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009475700","display_name":"Stavros Petridis","orcid":"https://orcid.org/0000-0001-7478-9479"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Petridis, Stavros","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016033078","display_name":"Maja Panti\u0107","orcid":"https://orcid.org/0000-0002-3620-5986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pantic, Maja","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5042231269","display_name":"Naomi Harte","orcid":"https://orcid.org/0000-0002-9274-209X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harte, Naomi","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/T10860","display_name":"Speech and Audio Processing","score":0.9478999972343445,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9478999972343445,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.021800000220537186,"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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.014399999752640724,"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/set","display_name":"Set (abstract data type)","score":0.6692000031471252},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6093999743461609},{"id":"https://openalex.org/keywords/raising","display_name":"Raising (metalworking)","score":0.4878000020980835},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.4487999975681305},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.436599999666214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6825000047683716},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6692000031471252},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5218999981880188},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4961000084877014},{"id":"https://openalex.org/C2780589192","wikidata":"https://www.wikidata.org/wiki/Q7285140","display_name":"Raising (metalworking)","level":2,"score":0.4878000020980835},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4781000018119812},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34439998865127563},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.2919999957084656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07259","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07259","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,"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.2606.07259","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07259","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,"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Current":[0],"Audio-Visual":[1],"Speech":[2],"Recognition":[3],"(AVSR)":[4],"models":[5],"achieve":[6],"near-perfect":[7],"performance":[8,64,110],"on":[9],"the":[10,34,46,53,88],"standard":[11,39],"LRS3":[12,54],"benchmark,":[13],"raising":[14],"concerns":[15],"of":[16,52,91],"adaptive":[17],"overfitting.":[18],"To":[19],"systematically":[20],"assess":[21],"true":[22],"generalisability,":[23],"we":[24,86,95],"construct":[25],"a":[26,62,79,97],"highly":[27],"controlled,":[28],"unseen":[29],"evaluation":[30],"set":[31,121],"subsampled":[32],"from":[33],"massive":[35],"MultiVSR":[36],"dataset.":[37],"Unlike":[38],"out-of-distribution":[40],"benchmarks,":[41],"our":[42,118],"subset":[43],"strictly":[44,75],"matches":[45],"acoustic,":[47],"visual,":[48],"and":[49,105],"demographic":[50],"distributions":[51],"test":[55,120],"set.":[56],"Evaluating":[57],"five":[58],"state-of-the-art":[59],"architectures":[60],"reveals":[61],"universal":[63],"collapse,":[65],"proving":[66],"that":[67,108],"current":[68],"systems":[69],"fail":[70],"to":[71],"generalise":[72],"even":[73,111],"under":[74],"aligned":[76],"conditions.":[77],"Through":[78],"fine-grained":[80],"attribute":[81],"analysis":[82],"across":[83],"seven":[84],"factors,":[85],"isolate":[87],"specific":[89],"drivers":[90],"this":[92],"degradation.":[93],"Furthermore,":[94],"uncover":[96],"profound":[98],"lexical":[99],"bias,":[100],"expose":[101],"distinct":[102],"error":[103],"patterns,":[104],"surprisingly":[106],"reveal":[107],"audio-visual":[109],"lags":[112],"behind":[113],"audio-only":[114],"settings.":[115],"We":[116],"release":[117],"matched":[119],"for":[122],"future":[123],"benchmarking.":[124]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-09T00:00:00"}