Clematide, Simon

Ströbel, Phillip

Ströbel, Phillip Benjamin

ZORA

Zurich Open Repository andArchiveUniversity of ZurichMain LibraryStrickhofstrasse 39CH-8057 Zurichwww.zora.uzh.chYear: 2018Improving OCR quality of Historical Newspapers with Handwritten TextRecognition ModelsClematide, Simon; Ströbel, PhillipPosted at the Zurich Open Repository and Archive, University of ZurichZORA URL: https://doi.org/10.5167/uzh-167932Conference or Workshop ItemAccepted Version  The following work is licensed under a Creative Commons: Attribution 1.0 Generic (CC BY 1.0) License.Originally published at:Clematide, Simon; Ströbel, Phillip (2018). Improving OCR quality of Historical Newspapers with Hand-written Text Recognition Models. In: Workshop DARIAH-CH, Neuchâtel, 29 November 2018 - 30November 2018.Year OCR-2005 OCR-2017 HTR-20181799 0.752 0.861 0.9671819 0.424 0.620 0.9761859 0.529 0.802 0.9711879 0.747 0.918 0.979Collection 80267 - HR images from ZB, year 1899Page ABBYY - WER HTR-2018 - WERABBYY - CER HTR-2018 - CER ABBY-BOWF HTR-2018-BOWFp6 5.94 2.79 1.29 0.70 0.95 0.98p90 5.44 2.14 1.17 0.66 0.96 0.98p162 8.81 4.70 2.14 2.01 0.94 0.97 title pagep376 9.53 6.24 2.42 2.55 0.93 0.96 title pagep422 5.03 2.82 1.42 0.99 0.96 0.98AVERAGE 6.95 3.74 1.69 1.38 0.95 0.97HTR abs improv 3.212 0.307 0.025HTR rel err red by 46.2% 18.2% 47.57%INVOLVES » computational linguists » digital humanists » historians » web designersTHEIR COMMON GOAL » tackling the challenges of content enrich-ment and data representation, visualiza-tion and analysis, completed by method-ological and epistemological reflectionsEXPECTED OUTCOMES » natural language processing (NLP) tools dedicated to historical print media writ-ten in French and German » visualization interfaces for active and goal-oriented exploration and critical analysis of newspaper corpora » an application of digital history research on resistance to European integration.   » bag-of-words f-measure evaluation with TextEval 1.4  » www.primaresearch.org/tools/PerformanceEvaluation » compare three different outputs » original OCR by NZZ (ocr-2005) » re-OCRised material using ABBYY Finereader2 (ocr-2017) » Transkribus’ HTR model (htr-2018) » HTR models significantly increase OCR quality » relatively small gold standards for training purposes suffice for de-cent OCR » better OCR is beneficial for text mining techniquesOpen questions: » Do the HTR models trained on the NZZ perform equally well on oth-er newspapers? » How does occasionally occurring text in antiqua affect OCR quality?LAUSANNE, LUXEMBOURG, ZURICH / THURSDAY, NOVEMBER 29TH, 2018 FREE / OPEN-SOURCENº 0001Overall impresso pipeline OCR QUALITY OF HISTORICAL NEWSPAPERSTACKLING OCR WITH HTR TOOLSEVALUATION AND COMPARISONDISCUSSION & OUTLOOKSurprising success: Researchers report astonishing OCR results on historical newspapers!Main objective: enabling critical text mining to search, extract, process, link, and explore data from print media archives via a unified web interface,»!’’ ‘.’’., ,!^ WWW’ ütchM ^ !’’i: ...Me» in l^t Ms«ndlM »edr»cks»n>; ‘!” ‘« ‘.IH, ! ‘,’ Großbrit«».««!.. .chOwtdf^.WnM««.. Hz<;ntschl«!»d,liN!ii.ung»Ntim Norden.^ Königes pou Isq.M’»«.^«!^^..^»««^«»’^ Prand »u., Debr«in). .Fl«nkl<;lch (Dü-niouri« letzter Uuf»ll. Edle Vnft«lt lu^ «««ch). Gchwell WMatssM , ‘ G r Zu lioZddn ‘«tstvtbe... «iß ,-.u»ch <;» ß HZ l«,«‘» «il <; n.’ 5 welGs/ich EN). s«ellen»’lü Mtlie». habt/ Iso« Hob Ihre« «i»!«»«»..»..,’ di« Kapirin bewiest«» «apfet. eit ihm unsre Newunderun« «wer-ben h,«l”, ünd wege» des, bittet , stu traMjlen M^etben« die «im». Vesttzü..« mi«d bezeugen.- es <;3t«llt».^1MTheil-nahck^ in Zw. Äbl^ gefiel prMMM ili H. «r« L» »ar lmIaM.M.’«^«. AHstebdä.« MniH «Mai»? b?«^ - >;«.ige«^ ? d«<; fi« «uf .z. MM«,«« O«d«n «iNluft, erb. demÄll-maWgtt. ihn ‘,u ffch/y» neumen/’ u«t» ei lockmt i,s« stiiltl iu, wenn Auch «icht bhn^HWintt/boHM’S^^ stin t»d»P-tirtel<;S«h«, -Willia«. H<;l^>;e>; » 167 front pages from the Neue Zürcher Zeitung (NZZ) » we used Transkribus1 to create a gold standard » manual correction of words and baselines » training of Handwritten Text » Recognition (HTR) model within » Transkribus with 158 pages1 https://www.transkribus.eu 2 https://www.abbyy.comC O N T A C T  P E R S O N SSimon Clematide, UZHMarten Düring, C2DHMaud Ehrmann, EPFLS T A Y  C O N N E C T E Dhttps://impresso-project.chinfo@impresso-project.cht w i t t e r  @ImpressoProjectgrant n° CR- SII5_173719 supervisors  Fréderic Kaplan, EPFL - Andreas Fickers, C2DH - Martin Volk, UZH collaborators  Thijs van Beek - Estelle Bunout, PhD - Daniele Guido, M.Sc. - Matteo Romanello, PhD - Paul Schroeder - Phillip Ströbel, M.A.

Improving OCR quality of Historical Newspapers with Handwritten Text Recognition Models

https://www.zora.uzh.ch/id/eprint/167932/1/poster_daria-ch_impresso.pdf

Improving OCR quality of Historical Newspapers with Handwritten Text Recognition Models

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