{"id":"https://openalex.org/W7168262320","doi":"https://doi.org/10.48550/arxiv.2607.09833","title":"Generative Testing of Automated Speech Recognition Systems","display_name":"Generative Testing of Automated Speech Recognition Systems","publication_year":2026,"publication_date":"2026-07-10","ids":{"openalex":"https://openalex.org/W7168262320","doi":"https://doi.org/10.48550/arxiv.2607.09833"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.09833","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.09833","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.2607.09833","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140586590","display_name":"Yanis Xabier Wilbrand Pe\u00f1a","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pe\u00f1a, Yanis Xabier Wilbrand","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140668619","display_name":"Oliver Wei\u00dfl","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei\u00dfl, Oliver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140703106","display_name":"Andrea Stocco","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stocco, Andrea","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8385000228881836,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8385000228881836,"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":0.08100000023841858,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.007499999832361937,"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/perception","display_name":"Perception","score":0.48089998960494995},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4648999869823456},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4108000099658966},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4036000072956085},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.3425999879837036},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.33000001311302185},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.3176000118255615},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3160000145435333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7642999887466431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5278000235557556},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4648999869823456},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4318000078201294},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4108000099658966},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.33000001311302185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3278999924659729},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.3176000118255615},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.09833","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.09833","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.2607.09833","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.09833","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":[{"id":"https://metadata.un.org/sdg/16","score":0.6047913432121277,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automatic":[0],"speech":[1],"recognition":[2],"(ASR)":[3],"systems":[4],"have":[5],"achieved":[6],"high":[7],"accuracy":[8],"with":[9],"transformer-based":[10],"models,":[11],"enabling":[12],"deployment":[13],"in":[14,25,49],"critical":[15,145],"applications.":[16],"However,":[17],"they":[18],"remain":[19],"vulnerable":[20],"to":[21,69,148],"adversarial":[22],"manipulation,":[23],"particularly":[24],"black-box":[26,39,103],"settings":[27],"where":[28],"attacks":[29],"must":[30],"preserve":[31],"perceptual":[32,94,119,141],"naturalness.":[33],"This":[34],"work":[35],"introduces":[36],"GATAS,":[37],"a":[38,55,86,109],"testing":[40],"approach":[41,65],"that":[42,106,138,155],"generates":[43],"failure":[44],"inducing":[45],"inputs":[46],"by":[47,123],"operating":[48,127],"the":[50,64,76,160],"phoneme-level":[51],"latent":[52,67],"space":[53],"of":[54,60,78,163],"text-":[56],"to-speech":[57],"model.":[58],"Instead":[59],"perturbing":[61],"waveforms":[62],"directly,":[63],"interpolates":[66],"representations":[68],"induce":[70],"transcription":[71],"errors":[72],"while":[73,113],"remaining":[74],"within":[75],"manifold":[77],"natural":[79],"speech.":[80],"The":[81],"attack":[82],"is":[83],"formulated":[84],"as":[85,121],"multi-objective":[87],"optimization":[88,158],"problem":[89],"balancing":[90],"semantic":[91],"divergence":[92],"and":[93,102,117,140,165],"quality.":[95],"Our":[96],"empirical":[97],"evaluation":[98],"against":[99,134],"both":[100],"white-box":[101,135],"baselines":[104],"shows":[105],"GATAS":[107,131],"achieves":[108],"98%":[110],"success":[111],"rate":[112],"producing":[114],"lower":[115],"distortion":[116],"higher":[118],"quality,":[120],"confirmed":[122],"human":[124],"studies.":[125],"Despite":[126],"without":[128],"gradient":[129],"access,":[130],"remains":[132],"competitive":[133],"methods,":[136],"highlighting":[137],"representation":[139],"alignment":[142],"are":[143],"more":[144],"than":[146],"access":[147],"model":[149],"internals.":[150],"Overall,":[151],"our":[152],"results":[153],"demonstrate":[154],"untargeted":[156],"latent-space":[157],"enables":[159],"efficient":[161],"generation":[162],"realistic":[164],"effective":[166],"test":[167],"cases":[168],"for":[169],"ASR":[170],"systems.":[171]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}