A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources
This article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest seri...
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| Format: | Article |
| Language: | English |
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International Institute of Social History
2015-01-01
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| Series: | Historical Life Course Studies |
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| Online Access: | https://www.openjournals.nl/index.php/hlcs/article/view/9355 |
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| author | Gunnar Thorvaldsen Joana Maria Pujadas-Mora Trygve Andersen Line Eikvil Josep Lladós Alícia Fornés Anna Cabré |
| author_facet | Gunnar Thorvaldsen Joana Maria Pujadas-Mora Trygve Andersen Line Eikvil Josep Lladós Alícia Fornés Anna Cabré |
| author_sort | Gunnar Thorvaldsen |
| collection | DOAJ |
| description | This article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest series of preserved vital records. Thus, in the Project “Five Centuries of Marriages” (5CofM) at the Autonomous University of Barcelona’s Center for Demographic Studies, the Barcelona Historical Marriage Database has been built. More than 600,000 records were transcribed by 150 transcribers working online. The Norwegian material is cross-sectional as it is the 1891 census, recorded on one sheet per person. This format and the underlining of keywords for several variables made it more feasible to semi-automate data entry than when many persons are listed on the same page. While Optical Character Recognition (OCR) for printed text is scientifically mature, computer vision research is now focused on more difficult problems such as handwriting recognition. In the marriage project, document analysis methods have been proposed to automatically recognize the marriage licenses. Fully automatic recognition is still a challenge, but some promising results have been obtained. In Spain, Norway and elsewhere the source material is available as scanned pictures on the Internet, opening up the possibility for further international cooperation concerning automating the transcription of historic source materials. Like what is being done in projects to digitize printed materials, the optimal solution is likely to be a combination of manual transcription and machine-assisted recognition also for hand-written sources. |
| format | Article |
| id | doaj-art-071e12e9b86c4e168dca545b8915346c |
| institution | Kabale University |
| issn | 2352-6343 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | International Institute of Social History |
| record_format | Article |
| series | Historical Life Course Studies |
| spelling | doaj-art-071e12e9b86c4e168dca545b8915346c2025-02-02T13:13:40ZengInternational Institute of Social HistoryHistorical Life Course Studies2352-63432015-01-01210.51964/hlcs9355A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical SourcesGunnar ThorvaldsenJoana Maria Pujadas-MoraTrygve AndersenLine EikvilJosep LladósAlícia FornésAnna CabréThis article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest series of preserved vital records. Thus, in the Project “Five Centuries of Marriages” (5CofM) at the Autonomous University of Barcelona’s Center for Demographic Studies, the Barcelona Historical Marriage Database has been built. More than 600,000 records were transcribed by 150 transcribers working online. The Norwegian material is cross-sectional as it is the 1891 census, recorded on one sheet per person. This format and the underlining of keywords for several variables made it more feasible to semi-automate data entry than when many persons are listed on the same page. While Optical Character Recognition (OCR) for printed text is scientifically mature, computer vision research is now focused on more difficult problems such as handwriting recognition. In the marriage project, document analysis methods have been proposed to automatically recognize the marriage licenses. Fully automatic recognition is still a challenge, but some promising results have been obtained. In Spain, Norway and elsewhere the source material is available as scanned pictures on the Internet, opening up the possibility for further international cooperation concerning automating the transcription of historic source materials. Like what is being done in projects to digitize printed materials, the optimal solution is likely to be a combination of manual transcription and machine-assisted recognition also for hand-written sources.https://www.openjournals.nl/index.php/hlcs/article/view/9355Word spottingOptical Character RecognitionVital recordsCensusNominative sourcesComputer vision |
| spellingShingle | Gunnar Thorvaldsen Joana Maria Pujadas-Mora Trygve Andersen Line Eikvil Josep Lladós Alícia Fornés Anna Cabré A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources Historical Life Course Studies Word spotting Optical Character Recognition Vital records Census Nominative sources Computer vision |
| title | A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources |
| title_full | A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources |
| title_fullStr | A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources |
| title_full_unstemmed | A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources |
| title_short | A Tale of Two Transcriptions. Machine-Assisted Transcription of Historical Sources |
| title_sort | tale of two transcriptions machine assisted transcription of historical sources |
| topic | Word spotting Optical Character Recognition Vital records Census Nominative sources Computer vision |
| url | https://www.openjournals.nl/index.php/hlcs/article/view/9355 |
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