{"id":"https://openalex.org/W7158555352","doi":"https://doi.org/10.48550/arxiv.2604.26676","title":"A Toolkit for Detecting Spurious Correlations in Speech Datasets","display_name":"A Toolkit for Detecting Spurious Correlations in Speech Datasets","publication_year":2026,"publication_date":"2026-04-29","ids":{"openalex":"https://openalex.org/W7158555352","doi":"https://doi.org/10.48550/arxiv.2604.26676"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.26676","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26676","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":null,"license_id":null,"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.2604.26676","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014439463","display_name":"Lara Gauder","orcid":"https://orcid.org/0000-0001-6242-1546"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gauder, Lara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031932671","display_name":"Pablo Riera","orcid":"https://orcid.org/0000-0001-8570-4688"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Riera, Pablo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134878629","display_name":"Andrea Slachevsky","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Slachevsky, Andrea","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033608682","display_name":"Gonzalo Forno","orcid":"https://orcid.org/0000-0003-2739-6028"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Forno, Gonzalo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134898336","display_name":"Adolfo M. Garc\u00eda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garc\u00eda, Adolfo M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056267912","display_name":"Luciana Ferrer","orcid":"https://orcid.org/0000-0002-0426-8683"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ferrer, Luciana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5014439463"],"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":0.4212000072002411,"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":0.4212000072002411,"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":0.149399995803833,"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/T11309","display_name":"Music and Audio Processing","score":0.11330000311136246,"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/spurious-relationship","display_name":"Spurious relationship","score":0.9710000157356262},{"id":"https://openalex.org/keywords/flagging","display_name":"Flagging","score":0.9175000190734863},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6549999713897705},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6485000252723694},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3434999883174896}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.9710000157356262},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.9175000190734863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7527999877929688},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6549999713897705},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6485000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43470001220703125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3783000111579895},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3765999972820282},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3635999858379364},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.26676","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26676","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.26676","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26676","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5615752339363098}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,26,52,71],"toolkit":[3,69,118],"for":[4,29,122],"uncovering":[5],"spurious":[6,115],"correlations":[7,18,42],"between":[8],"recording":[9,24],"characteristics":[10],"and":[11,38],"target":[12,80,102],"class":[13,81,103],"in":[14,35,44,56,87],"speech":[15],"datasets.":[16,31],"Spurious":[17],"may":[19],"arise":[20],"due":[21],"to":[22,63],"heterogeneous":[23],"conditions,":[25],"common":[27],"scenario":[28],"health-related":[30],"When":[32],"present":[33],"both":[34],"the":[36,48,76,79,84,88,101,108,112],"training":[37],"test":[39],"data,":[40],"these":[41],"result":[43],"an":[45],"overestimation":[46],"of":[47,78,114],"system":[49],"performance":[50,66,93],"--":[51],"dangerous":[53],"situation,":[54],"specially":[55],"high-stakes":[57],"application":[58],"where":[59],"systems":[60],"are":[61],"required":[62],"satisfy":[64],"minimum":[65],"requirements.":[67],"Our":[68],"implements":[70],"diagnostic":[72],"method":[73],"based":[74],"on":[75],"detection":[77],"using":[82],"only":[83],"non-speech":[85,109],"regions":[86],"audio.":[89],"Better":[90],"than":[91],"chance":[92],"at":[94],"this":[95],"task":[96],"indicates":[97],"that":[98],"information":[99],"about":[100],"can":[104],"be":[105],"extracted":[106],"from":[107],"regions,":[110],"flagging":[111],"presence":[113],"correlations.":[116],"The":[117],"is":[119],"publicly":[120],"available":[121],"research":[123],"use.":[124]},"counts_by_year":[],"updated_date":"2026-05-04T08:30:34.212998","created_date":"2026-05-01T00:00:00"}
