{"id":"https://openalex.org/W7204854727","doi":"https://doi.org/10.18653/2026.findings-emnlp.1056","title":"A Shaky Voice Is Not Always a Dodge: Benchmarking Textual and Vocal Evasion Detection in Earnings Calls","display_name":"A Shaky Voice Is Not Always a Dodge: Benchmarking Textual and Vocal Evasion Detection in Earnings Calls","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204854727","doi":"https://doi.org/10.18653/2026.findings-emnlp.1056"},"language":"en","primary_location":{"id":"doi:10.18653/2026.findings-emnlp.1056","doi":"https://doi.org/10.18653/2026.findings-emnlp.1056","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.findings-emnlp.1056","pdf_url":"https://aclanthology.org/2026.findings-emnlp.1056.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2026","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://aclanthology.org/2026.findings-emnlp.1056.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126617815","display_name":"Mirae Kim","orcid":"https://orcid.org/0009-0000-3763-1189","observed_orcids":["https://orcid.org/0009-0000-3763-1189"]},"institutions":[{"id":"https://openalex.org/I4405259107","display_name":"Kakaobank (South Korea)","ror":"https://ror.org/01r9jj364","country_code":"KR","type":"company","lineage":["https://openalex.org/I4405259107","https://openalex.org/I4405259708"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mirae Kim","raw_affiliation_strings":["Financial Tech Lab , KakaoBank Corp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Financial Tech Lab , KakaoBank Corp","institution_ids":["https://openalex.org/I4405259107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126584078","display_name":"Seonghun Jeong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]},{"id":"https://openalex.org/I4405259107","display_name":"Kakaobank (South Korea)","ror":"https://ror.org/01r9jj364","country_code":"KR","type":"company","lineage":["https://openalex.org/I4405259107","https://openalex.org/I4405259708"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seonghun Jeong","raw_affiliation_strings":["Financial Tech Lab , KakaoBank Corp","Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Financial Tech Lab , KakaoBank Corp","institution_ids":["https://openalex.org/I4405259107"]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126618985","display_name":"Youngjun Kwak","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405259107","display_name":"Kakaobank (South Korea)","ror":"https://ror.org/01r9jj364","country_code":"KR","type":"company","lineage":["https://openalex.org/I4405259107","https://openalex.org/I4405259708"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngjun Kwak","raw_affiliation_strings":["Financial Tech Lab , KakaoBank Corp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Financial Tech Lab , KakaoBank Corp","institution_ids":["https://openalex.org/I4405259107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22366","last_page":"22377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.21950000524520874,"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":0.21950000524520874,"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/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.1225999966263771,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.08169999718666077,"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/earnings-calls","display_name":"earnings conference calls","score":0.9879999756813049},{"id":"https://openalex.org/keywords/speaker-confidence","display_name":"speaker confidence","score":0.6119999885559082},{"id":"https://openalex.org/keywords/vocal-cues","display_name":"vocal cues","score":0.9210000038146973},{"id":"https://openalex.org/keywords/multimodal-benchmark","display_name":"multimodal benchmark","score":0.6959999799728394},{"id":"https://openalex.org/keywords/executive-speech","display_name":"executive speech","score":0.3440000116825104},{"id":"https://openalex.org/keywords/question-answer-pairs","display_name":"question-answer pairs","score":0.6320000290870667},{"id":"https://openalex.org/keywords/acoustic-characteristics","display_name":"acoustic features","score":0.5389999747276306},{"id":"https://openalex.org/keywords/multimodal-models","display_name":"multimodal models","score":0.6240000128746033}],"concepts":[{"id":"https://openalex.org/C2781251061","wikidata":"https://www.wikidata.org/wiki/Q5416089","display_name":"Evasion (ethics)","level":3,"score":0.8166000247001648},{"id":"https://openalex.org/C2781426361","wikidata":"https://www.wikidata.org/wiki/Q5326940","display_name":"Earnings","level":2,"score":0.7484999895095825},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.5626000165939331},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.560699999332428},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5595999956130981},{"id":"https://openalex.org/C2779777834","wikidata":"https://www.wikidata.org/wiki/Q4202277","display_name":"Enforcement","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42289999127388},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4101000130176544},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.34790000319480896},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3253999948501587},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.30570000410079956},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C2989421709","wikidata":"https://www.wikidata.org/wiki/Q6502151","display_name":"Tax evasion","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.29280000925064087},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.28760001063346863},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.28630000352859497},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2824999988079071},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.27129998803138733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2522999942302704}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.findings-emnlp.1056","doi":"https://doi.org/10.18653/2026.findings-emnlp.1056","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.findings-emnlp.1056","pdf_url":"https://aclanthology.org/2026.findings-emnlp.1056.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.28040","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28040","pdf_url":"https://arxiv.org/pdf/2608.28040","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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28040","doi":"https://doi.org/10.48550/arxiv.2608.28040","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28040","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":"doi:10.18653/2026.findings-emnlp.1056","doi":"https://doi.org/10.18653/2026.findings-emnlp.1056","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.findings-emnlp.1056","pdf_url":"https://aclanthology.org/2026.findings-emnlp.1056.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204854727.pdf","grobid_xml":"https://content.openalex.org/works/W7204854727.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W7124299704","https://openalex.org/W7166884177"],"related_works":["https://openalex.org/W7213311775","https://openalex.org/W7172353584","https://openalex.org/W7154728522","https://openalex.org/W3089609471","https://openalex.org/W7133285311","https://openalex.org/W7171748428","https://openalex.org/W4241315393","https://openalex.org/W7169661484","https://openalex.org/W3095229993","https://openalex.org/W3175941745"],"abstract_inverted_index":{"Existing":[0],"approaches":[1],"to":[2,97,117],"evasion":[3,13,20,50,76],"detection":[4,51],"in":[5,21,56,112],"earnings":[6,57,68],"calls":[7],"focus":[8],"on":[9,102],"textual":[10,75],"transcripts,":[11],"treating":[12],"as":[14,84],"a":[15,47,127],"single-dimensional":[16],"phenomenon.We":[17],"argue":[18],"that":[19,92],"spoken":[22],"communication":[23],"is":[24],"inherently":[25],"multidimensional:":[26],"beyond":[27],"what":[28],"executives":[29],"say,":[30],"how":[31],"they":[32],"say":[33],"it":[34],"carries":[35],"independent":[36,73],"and":[37,54,80],"complementary":[38],"information.To":[39],"study":[40],"these":[41,107],"dimensions":[42],"jointly,":[43],"we":[44],"introduce":[45],"DualEvasion,":[46],"benchmark":[48,60],"for":[49],"across":[52],"text":[53],"audio":[55],"call":[58],"Q&A.The":[59],"contains":[61],"505":[62],"annotated":[63],"question-answer":[64],"pairs":[65],"from":[66],"60":[67],"calls,":[69],"each":[70,118],"with":[71,130],"two":[72],"labels:":[74],"(direct":[77],"vs.":[78,88],"evasive)":[79],"vocal":[81,99],"cues":[82,111],"operationalized":[83],"speaker":[85],"confidence":[86],"(confident":[87],"unconfident).Our":[89],"experiments":[90],"show":[91],"state-of-the-art":[93],"multimodal":[94],"models":[95,108],"struggle":[96],"detect":[98],"confidence,":[100],"particularly":[101],"unconfident":[103],"responses.Our":[104],"analysis":[105],"suggests":[106],"interpret":[109],"acoustic":[110],"isolation":[113],"rather":[114],"than":[115],"relative":[116],"speaker's":[119],"baseline.Providing":[120],"speaker-level":[121],"references":[122],"yields":[123],"modest":[124],"improvements,":[125],"but":[126],"substantial":[128],"gap":[129],"human":[131],"performance":[132],"remains.":[133]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-01T00:00:00"}