{"id":"https://openalex.org/W7126392810","doi":"https://doi.org/10.18653/v1/2024.latechclfl-1.25","title":"Direct Speech Identification in Swedish Literature and an Exploration of Training Data Type, Typographical Markers, and Evaluation Granularity","display_name":"Direct Speech Identification in Swedish Literature and an Exploration of Training Data Type, Typographical Markers, and Evaluation Granularity","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W7126392810","doi":"https://doi.org/10.18653/v1/2024.latechclfl-1.25"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2024.latechclfl-1.25","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.latechclfl-1.25","pdf_url":"https://aclanthology.org/2024.latechclfl-1.25.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2024.latechclfl-1.25.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124511360","display_name":"Sara Stymne","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sara Stymne","raw_affiliation_strings":["Department of Linguistics and Philology Uppsala University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Linguistics and Philology Uppsala University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5124511360"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4423684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"253","last_page":"263"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.48350000381469727,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.48350000381469727,"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/T11640","display_name":"Linguistic Variation and Morphology","score":0.0560000017285347,"subfield":{"id":"https://openalex.org/subfields/3310","display_name":"Linguistics and Language"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10403","display_name":"Phonetics and Phonology Research","score":0.03620000183582306,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6037999987602234},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.535099983215332},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5335000157356262},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.44679999351501465},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.27309998869895935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6791999936103821},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6037999987602234},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5620999932289124},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.535099983215332},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5335000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5275999903678894},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44530001282691956},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2599000036716461}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/2024.latechclfl-1.25","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.latechclfl-1.25","pdf_url":"https://aclanthology.org/2024.latechclfl-1.25.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:uu-545565","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-545565","pdf_url":"https://uu.diva-portal.org/smash/get/diva2:1922222/FULLTEXT01","source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.latechclfl-1.25","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.latechclfl-1.25","pdf_url":"https://aclanthology.org/2024.latechclfl-1.25.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7653995752334595,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G8869864247","display_name":"NAISS","funder_award_id":"2022-06725","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"}],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"},{"id":"https://openalex.org/F4320336376","display_name":"Uppsala Multidisciplinary Center for Advanced Computational Science","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126392810.pdf","grobid_xml":"https://content.openalex.org/works/W7126392810.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Identifying":[0],"direct":[1,44],"speech":[2,14,76,132],"in":[3],"literary":[4,90],"fiction":[5],"is":[6,138],"challenging":[7],"for":[8,141],"cases":[9],"that":[10,94,128,137],"do":[11],"not":[12,148],"mark":[13],"segments":[15],"with":[16,40,103],"quotation":[17,41],"marks.Such":[18],"efforts":[19],"have":[20],"previously":[21],"been":[22,49],"based":[23],"either":[24],"on":[25,88,109,119],"smaller":[26],"manually":[27],"annotated":[28,34],"gold":[29,96,104],"data":[30,99,105,114,124,127,155],"or":[31],"larger":[32],"automatically":[33],"silver":[35,98,113],"data,":[36],"extracted":[37],"from":[38],"works":[39],"marks.However,":[42],"no":[43],"comparison":[45],"has":[46,100,116],"so":[47],"far":[48],"made":[50],"between":[51],"the":[52,69,122,130,135,153],"performance":[53],"of":[54,58,71,74,79,83,134,160],"these":[55],"two":[56],"types":[57,73,159],"training":[59,123,154],"data.In":[60],"this":[61,65],"work,":[62],"we":[63],"address":[64],"gap.We":[66],"further":[67],"explore":[68],"effect":[70],"different":[72,84,101],"typographical":[75,131],"marking":[77,133],"and":[78,92,97],"using":[80,95],"evaluation":[81],"metrics":[82],"granularity.We":[85],"perform":[86],"experiments":[87],"Swedish":[89],"texts":[91],"find":[93],"strengths,":[102],"having":[106],"stronger":[107,117],"results":[108,118],"token-level":[110],"metrics,":[111],"whereas":[112],"overall":[115],"span-level":[120],"metrics.If":[121],"contains":[125,157],"some":[126],"matches":[129],"target,":[136],"generally":[139],"sufficient":[140],"achieving":[142],"good":[143],"results,":[144],"but":[145],"it":[146],"does":[147],"seem":[149],"to":[150],"hurt":[151],"if":[152],"also":[156],"other":[158],"marking.":[161]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-02-02T00:00:00"}
