{"id":"https://openalex.org/W4402590041","doi":"https://doi.org/10.1145/3685650.3685669","title":"Post-OCR Correction with OpenAI's GPT Models on Challenging English Prosody Texts","display_name":"Post-OCR Correction with OpenAI's GPT Models on Challenging English Prosody Texts","publication_year":2024,"publication_date":"2024-08-20","ids":{"openalex":"https://openalex.org/W4402590041","doi":"https://doi.org/10.1145/3685650.3685669"},"language":"en","primary_location":{"id":"doi:10.1145/3685650.3685669","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3685650.3685669","pdf_url":null,"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 ACM Symposium on Document Engineering 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3685650.3685669","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100296236","display_name":"James Zhang","orcid":"https://orcid.org/0009-0002-6703-8647"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"James Zhang","raw_affiliation_strings":["Department of Computer Science, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Princeton, New Jersey, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037450666","display_name":"Wouter Haverals","orcid":"https://orcid.org/0000-0002-5687-6787"},"institutions":[{"id":"https://openalex.org/I4210110242","display_name":"Digital Science (United States)","ror":"https://ror.org/020h4b682","country_code":"US","type":"company","lineage":["https://openalex.org/I4210110242","https://openalex.org/I4210112888","https://openalex.org/I4210118830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wouter Haverals","raw_affiliation_strings":["Center for Digital Humanities, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Center for Digital Humanities, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210110242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057434243","display_name":"Mary Naydan","orcid":"https://orcid.org/0000-0002-7960-3175"},"institutions":[{"id":"https://openalex.org/I4210110242","display_name":"Digital Science (United States)","ror":"https://ror.org/020h4b682","country_code":"US","type":"company","lineage":["https://openalex.org/I4210110242","https://openalex.org/I4210112888","https://openalex.org/I4210118830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mary Naydan","raw_affiliation_strings":["Center for Digital Humanities, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Center for Digital Humanities, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210110242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034540227","display_name":"Brian W. Kernighan","orcid":"https://orcid.org/0000-0003-0741-9085"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brian W. Kernighan","raw_affiliation_strings":["Department of Computer Science, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Princeton, New Jersey, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100296236"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8131,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87449051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9961000084877014,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9961000084877014,"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6031107902526855},{"id":"https://openalex.org/keywords/prosody","display_name":"Prosody","score":0.5507175326347351},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5223175883293152},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.49522820115089417},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.4798657298088074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43301984667778015},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.10166189074516296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6031107902526855},{"id":"https://openalex.org/C542774811","wikidata":"https://www.wikidata.org/wiki/Q10880526","display_name":"Prosody","level":2,"score":0.5507175326347351},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5223175883293152},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.49522820115089417},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.4798657298088074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43301984667778015},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.10166189074516296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3685650.3685669","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3685650.3685669","pdf_url":null,"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 ACM Symposium on Document Engineering 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3685650.3685669","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3685650.3685669","pdf_url":null,"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 ACM Symposium on Document Engineering 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2767199627","https://openalex.org/W4320167623","https://openalex.org/W4322760121","https://openalex.org/W4385820319","https://openalex.org/W4385964810","https://openalex.org/W4389116462","https://openalex.org/W4390307319"],"related_works":["https://openalex.org/W2355553914","https://openalex.org/W149862513","https://openalex.org/W2347684782","https://openalex.org/W4320472397","https://openalex.org/W2401269021","https://openalex.org/W2145654520","https://openalex.org/W2750037515","https://openalex.org/W4319862652","https://openalex.org/W2394249171","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0,102],"digitization":[1],"of":[2,10,18,32,131],"historical":[3],"documents":[4],"faces":[5],"challenges":[6],"with":[7,86,108,117],"the":[8,16,30,40,47,96,118,123,151],"accuracy":[9],"Optical":[11],"Character":[12,124],"Recognition":[13],"(OCR).":[14],"Noting":[15],"success":[17],"large":[19],"language":[20],"models":[21,35,103],"(LLMs)":[22],"on":[23,39,64,146],"many":[24],"text-based":[25],"tasks,":[26],"this":[27],"paper":[28],"explores":[29],"potential":[31],"OpenAI's":[33],"GPT":[34],"(3.5-turbo,":[36],"4,":[37],"4-turbo)":[38],"post-OCR":[41],"correction":[42],"task":[43],"using":[44],"works":[45,107],"from":[46],"Princeton":[48],"Prosody":[49],"Archive":[50],"(PPA),":[51],"a":[52,70,129,136],"full-text":[53],"searchable":[54],"database":[55],"containing":[56],"English":[57],"texts":[58,143],"published":[59],"between":[60],"1559":[61],"and":[62,66,77],"1928":[63],"versification":[65],"pronunciation.":[67],"We":[68],"conduct":[69],"comparative":[71],"analysis":[72],"across":[73],"different":[74],"model":[75,120],"configurations":[76],"prompt":[78],"strategies.":[79],"Our":[80],"results":[81],"indicate":[82],"that":[83],"tailoring":[84],"prompts":[85],"work":[87],"metadata":[88],"is":[89],"less":[90],"effective":[91],"than":[92],"anticipated,":[93],"though":[94],"adjusting":[95],"temperature":[97],"parameter":[98],"can":[99],"be":[100],"beneficial.":[101],"tend":[104],"to":[105,141,156],"overcorrect":[106],"already":[109],"good":[110],"OCR":[111,149],"quality":[112,138],"but":[113],"perform":[114],"well":[115],"overall,":[116],"best":[119,152],"setup":[121],"improving":[122],"Error":[125],"Rate":[126],"(CER)":[127],"by":[128],"mean":[130,153],"18.92%.":[132],"Additionally,":[133],"after":[134],"introducing":[135],"preliminary":[137],"estimation":[139],"step":[140],"process":[142],"differently":[144],"based":[145],"their":[147],"original":[148],"quality,":[150],"improvement":[154],"increases":[155],"38.83%.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
